Publikationen
Key facts: 2.098 Veröffentlichungen (Stand Ende 2025) seit Gründung des SCCH 1999/2000, davon 1.595 reviewed Beiträge in Journalen, Tagungsbänden und Büchern. Am Zentrum wurden 3 Habilitationen, 71 Dissertationen und 106 Masterarbeiten abgeschlossen. In der aktuellen COMET Periode 2023-2026 wurden bisher 427 Beiträge veröffentlicht.
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2026
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A Web-Based Demonstrator for Quantum Circuit Programming Education
Schenkenfelder, B., Zefferer, R., & Wimmer, M.. (2026). A Web-Based Demonstrator for Quantum Circuit Programming Education. In Lecture Notes in Computer Science (pp. 329–332). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-29372-5_35
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Training Station: A Learning Ecosystem for an Inclusive AI Workforce
Schenkenfelder, B., Brandstätter, U., Toro Plaza, C. J., Márquez Ortega, G. P., Fischer, L., Hartl, M., Wurm, M., Außerlechner, R., & Laister, D.. (2026). Training Station: A Learning Ecosystem for an Inclusive AI Workforce. In Proceedings of the 2026 International Conference on Advanced Visual Interfaces (pp. 1–3). ACM. https://doi.org/10.1145/3811427.3811502
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AI-Assisted REST API Design with Large Language Models
Martinez-Gil, J., Daxerer, C., Winterer, M., Neumüller, C., & Krump, M.. (2026). AI-Assisted REST API Design with Large Language Models. In Lecture Notes in Business Information Processing (pp. 82–97). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-24216-7_5
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Automating Documentation of Complex Data Processing Flows with Large Language Models
Mahya, P., Martinez-Gil, J., Winterer, M., Neumüller, C., & Krump, M.. (2026). Automating Documentation of Complex Data Processing Flows with Large Language Models. In Lecture Notes in Business Information Processing (pp. 113–124). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-24216-7_7
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LLM Agents for Autonomous System Testing: A Semi-Structured Literature Review
Fischer, S., & Kloihofer, W.. (2026). LLM Agents for Autonomous System Testing: A Semi-structured Literature Review. In Lecture Notes in Business Information Processing (pp. 147–167). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-24216-7_9
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Proceedings of the 18th International Conference on Software Quality, SWQD 2026 (Software Architecture as the Backbone of Software Quality)
Software Architecture as the Backbone of Software Quality. (2026). Software Architecture as the Backbone of Software Quality. In Lecture Notes in Business Information Processing (p. None). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-24216-7
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ITEP4SDC at the SBFT 2026 Tool Competition: Self-Driving Car Testing Track
Gullu, A., Shah, F. A., & Pfahl, D.. (2026). ITEP4SDC at the SBFT 2026 Tool Competition: Self-Driving Car Testing Track. In Proceedings of the 19th ACM/IEEE International Workshop on Search-Based and Fuzz Testing (pp. 13–14). ACM. https://doi.org/10.1145/3786155.3795698
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Towards Multimodal Entity Linking for LLM-based Metamodel Generation
Schenkenfelder, B., & Wimmer, M.. (2026). Towards Multimodal Entity Linking for LLM-based Metamodel Generation. In Proceedings of the 2026 2nd International Workshop on Low-Code Development and Software Architecture (pp. 27–30). ACM. https://doi.org/10.1145/3786179.3788325
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Dataset for: TrainTicketTrace: A Multi-Fault Distributed Dataset for Microservice Fault Detection and Localization
Urbanke, P., & Fischer, S.. (2025). Dataset for: TrainTicketTrace: A Multi-Fault Distributed Dataset for Microservice Fault Detection and Localization [Data set]. In None (p. None). Zenodo. https://doi.org/10.5281/ZENODO.17811972
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Exploiting Space Folding by Neural Networks
Lewandowski, M., Pisoni, R., Heinzl, B., & Moser, B. A.. (2026). Exploiting Space Folding by Neural Networks. In Proceedings of the AAAI Conference on Artificial Intelligence (pp. 22833–22840). Association for the Advancement of Artificial Intelligence (AAAI). https://doi.org/10.1609/aaai.v40i27.39446
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Exploring Quantum Computing for Industrial Applications of Combinatorial Optimization: Structured Approach for Conducting Case Studies
Bruckner, S., Hillmich, S., Ramler, R., & Ferrarotti, F.. (2026). Exploring quantum computing for industrial applications of combinatorial optimization: structured approach for conducting case studies. In Proceedings of the 41st ACM/SIGAPP Symposium on Applied Computing (pp. 1394–1396). ACM. https://doi.org/10.1145/3748522.3779897
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AI-Driven Predictive Maintenance in Industrial IoTs: A Comprehensive Survey
Khan, M., Khan, M. A., Moser, B., Rafique, W., Xiaolong, X., & Wanchun, D.. (2026). AI-Driven Predictive Maintenance in Industrial IoTs: A Comprehensive Survey. In IEEE Internet of Things Journal (pp. 1–1). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/jiot.2026.3660780
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BROL: Cache-Only Execution for Software Protection
Mechelinck, R., & Volckaert, S.. (2026). BROL: Cache-Only Execution for Software Protection. In Proceedings of the Microarchitecture Security Conference (p. None). Universitatsbibliothek der Ruhr-Universitat Bochum. https://doi.org/10.46586/uasc.2026.004
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Investigating the Readability of Test Code: Combining Scientific and Practical View
Winkler, Dietmar; Urbanke, Pirmin; Ramler, Rudolf (2026): Investigating the Readability of Test Code: Combining Scientific and Practical View. SE2026. DOI: 10.18420/se2026_35. Gesellschaft für Informatik, Bonn. ISSN: 2944-7682
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Metamorphic Testing for Optimisation: A Case Study on PID Controller Tuning
Duque-Torres, Alejandra; Klammer, Claus; Fischer, Stefan; Ramler, Rudolf; Pfahl, Dietmar (2026): Metamorphic Testing for Optimisation: A Case Study on PID Controller Tuning. SE2026. DOI: 10.18420/se2026_40. Gesellschaft für Informatik, Bonn. ISSN: 2944-7682
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Smart-Digital-Twin-Framework zur Kostenoptimierung in der Recyclingindustrie
Duy, D. N., Meindl, S., Fonseca Diaz, V., Rainer, R., & Tischberger-Aldrian, A.. (2026). Smart-Digital-Twin-Framework zur Kostenoptimierung in der Recyclingindustrie. In Österreichische Wasser- und Abfallwirtschaft (pp. 144–150). Springer Science and Business Media LLC. https://doi.org/10.1007/s00506-026-01207-6
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Specialized Deep Residual Policy Safe Reinforcement Learning-Based Controller for Complex and Continuous State-Action Spaces
Abbas, A. N., Chasparis, G. C., & Kelleher, J. D.. (2026). Specialized Deep Residual Policy Reinforcement Learning Framework for Safe and Adaptive Continuous Control. In IET Control Theory & Applications (p. None). Institution of Engineering and Technology (IET). https://doi.org/10.1049/cth2.70099
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Integrating Quantum Software Tools with (in) MLIR
Hopf, P., Ochoa, E., Stade, Y., Rovara, D., Quetschlich, N., Florea, I. A., Izaac, J., Wille, R., & Burgholzer, L.. (2026). Integrating Quantum Software Tools with(in) MLIR. In Proceedings of the Supercomputing Asia and International Conference on High Performance Computing in Asia Pacific Region (pp. 42–54). ACM. https://doi.org/10.1145/3773656.3773658
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Mastering the Exponential Complexity of Exact Physical Simulation of Silicon Dangling Bonds
Lambooy, W., Drewniok, J., Walter, M., & Wille, R.. (2026). Mastering the Exponential Complexity of Exact Physical Simulation of Silicon Dangling Bonds. In 2026 31st Asia and South Pacific Design Automation Conference (ASP-DAC) (pp. 384–390). IEEE. https://doi.org/10.1109/asp-dac66049.2026.11420323
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Online appendix for a study on leveraging Multimodal Entity Linking (MEL) for LLM-based metamodel generation, submitted to the 2nd International Workshop on Low-Code Development and Software Architecture (LArc 2026).
Schenkenfelder, B., & Wimmer, M.. (2026). LArc 2026 [Data set]. In None (p. None). Zenodo. https://doi.org/10.5281/ZENODO.18298215
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Strategies for the Employment of People with Disabilities: A Scientific Perspective
Schenkenfelder, B., Brandstätter, U., Fischer, L., Ramler, R., Laister, D., Außerlechner, R., Hartl, M., & Wurm, M. (2026). Strategies for the Employment of People with Disabilities: A Scientific Perspective. In Carroll, N. (Ed.), Research Handbook on Digital Transformation and Responsibility (pp. 205-217). Edward Elgar Publishing.
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The Munich Quantum Software Stack: Connecting End Users, Integrating Diverse Quantum Technologies, Accelerating HPC
Burgholzer, L., Echavarria, J., Hopf, P., Stade, Y., Rovara, D., Schmid, L., Kaya, E., Mete, B., Farooqi, M. N., Chung, M., De Pascale, M., Schulz, L., Schulz, M., & Wille, R.. (2026). The Munich Quantum Software Stack: Connecting End Users, Integrating Diverse Quantum Technologies, Accelerating HPC. In Proceedings of the Supercomputing Asia and International Conference on High Performance Computing in Asia Pacific Region (pp. 55–67). ACM. https://doi.org/10.1145/3773656.3773669
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A Privacy-Preserving Approach for Collaborative Optimization Across Company Borders
Nguyen Duy, D., Fischer, B., Solina, V., & Affenzeller, M.. (2026). A Privacy‐Preserving Approach for Collaborative Optimization Across Company Borders. In IET Collaborative Intelligent Manufacturing (p. None). Institution of Engineering and Technology (IET). https://doi.org/10.1049/cim2.70063
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Behavioural Theory of Reflective Algorithms II: Reflective Parallel Algorithms.
Schewe, K.-D., & Ferrarotti, F.. (2026). Behavioural theory of reflective algorithms II: Reflective parallel algorithms. In Science of Computer Programming (p. 103505). Elsevier BV. https://doi.org/10.1016/j.scico.2026.103505
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Online appendix for a demonstration of the Training Station, submitted to the 18th International Conference on Advanced Visual Interfaces (AVI 2026)
Schenkenfelder, B.. (2026). AVI 2026 [Data set]. In None (p. None). Zenodo. https://doi.org/10.5281/ZENODO.19487433
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Online appendix for a demonstration of the Virtual Quantum Table, submitted to the 26th International Conference of Web Engineering (ICWE 2026).
Schenkenfelder, B., Zefferer, R., & Wimmer, M.. (2026). ICWE 2026 [Data set]. In None (p. None). Zenodo. https://doi.org/10.5281/ZENODO.19483346
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The Abstract State Machines Method
Ferrarotti, F., Gervasi, V., Raschke, A., & Schewe, K.-D.. (2026). The Abstract State Machines Method. In Formal Aspects of Computing (p. None). Association for Computing Machinery (ACM). https://doi.org/10.1145/3811032
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2025
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Automated Classification of ADS Disengagements Using Convolutional Neural Networks
Hein, E., Güllü, A. I., Shah, F. A., & Pfahl, D.. (2025). Automated Classification of ADS Disengagements Using Convolutional Neural Networks. In Lecture Notes in Computer Science (pp. 193–205). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-12092-2_14
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Large-scale stochastic simulation of open quantum systems
Sander, A., Fröhlich, M., Eigel, M., Eisert, J., Gelß, P., Hintermüller, M., Milbradt, R. M., Wille, R., & Mendl, C. B.. (2025). Large-scale stochastic simulation of open quantum systems. In Nature Communications (p. None). Springer Science and Business Media LLC. https://doi.org/10.1038/s41467-025-66846-x
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Obtaining Test Data in the Estonian e-Government System: Challenges and Improvement Potential
Tammisto, M.-A., Ramler, R., Shah, F. A., & Pfahl, D.. (2025). Obtaining Test Data in the Estonian E-Government System: Challenges and Improvement Potential. In Lecture Notes in Computer Science (pp. 3–18). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-12092-2_1
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Smart Twin: Ein Bayesisches Framework für die probabilistische Modellierung von mehrstufigen industriellen Prozessen
Meindl, S., Nguyen Duy, D., Diaz, V. F., Rainer, R., & Tischberger-Aldrian, A.. (2026). Smart Twin: Ein Bayessches Framework für die probabilistische Modellierung von mehrstufigen industriellen Prozessen. In Österreichische Wasser- und Abfallwirtschaft (p. None). Springer Science and Business Media LLC. https://doi.org/10.1007/s00506-026-01205-8
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Causally-Guided Pairwise Transformer - Towards Foundational Digital Twins in Process Industry
Mayr, M., & Chasparis, G. C.. (2026). Causally-Guided Pairwise Transformer - Towards Foundational Digital Twins in Process Industry. In Procedia Computer Science (pp. 175–184). Elsevier BV. https://doi.org/10.1016/j.procs.2026.02.059
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Explaining firefighters' technology acceptance: Findings from an Austrian cross-sectional study
Sandra Maria Pichler, Isabel Anger, Gerald Czech, Daniel Elias, Thomas Hütter, Georg Pilsner, Explaining firefighters’ technology acceptance: Findings from an Austrian cross-sectional study, International Journal of Disaster Risk Reduction, Volume 130, 2025, 105860, ISSN 2212-4209, https://doi.org/10.1016/j.ijdrr.2025.105860. (https://www.sciencedirect.com/science/article/pii/S2212420925006843) Abstract: Innovative firefighting technologies, such as unmanned aerial (UAVs) and ground vehicles (UGVs), present new opportunities for firefighting tactics and strategies. However, their practical implementation requires acceptance by end users. While technology acceptance has been extensively studied across various domains, technology acceptance by firefighters has received limited attention. This study addresses that gap by examining the drivers of individual technology acceptance in the firefighting domain. It applies a conceptual framework informed by the well-known Unified Theory of Acceptance and Use of Technology (UTAUT) model, as well as pioneering studies in the firefighting domain. Data were collected from an online survey among Austrian firefighters and analysed using regression analyses. The results demonstrate that the proposed framework significantly contributes to explaining firefighters’ willingness to use UAVs and UGVs. Subset variables of performance expectancy, effort expectancy, and social influence substantially contribute to the explanation, whereas control variables and facilitating conditions add little to the overall model fit. Notable differences were observed between the two technologies, with the model demonstrating a better fit for UAVs than for UGVs. Although most model variables were significantly correlated with both the willingness to use UAVs, and the willingness to use UGVs, regression analyses revealed that only a limited number of predictors made unique contributions to their explanation. The findings indicate the existence of both general acceptance factors—predictors that significantly influence the adoption of both UAVs and UGVs—and technology-specific acceptance factors—predictors that are uniquely associated with one of the two technologies. Keywords: Technology acceptance; Firefighting technology; UAVs; UGVs; Drones; Ground robots
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Joint Learning for Efficient German Argument Mining
Wendlinger, L., Kühn, R., Mitrović, J., & Granitzer, M.. (2025). Joint Learning for Efficient German Argument Mining. In 2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 770–777). IEEE. https://doi.org/10.1109/ictai66417.2025.00111
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OCCF - Leveraging Lagged Correlation Analysis for Enhanced Insights in Continuous Industrial Data
Luftensteiner, S., Krikova, K., & Rainer, R.. (2026). OCCF - Leveraging Lagged Correlation Analysis for Enhanced Insights in Continuous Industrial Data. In Procedia Computer Science (pp. 3655–3662). Elsevier BV. https://doi.org/10.1016/j.procs.2026.02.400
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Routing-Aware Placement for Zoned Neutral Atom-based Quantum Computing
Stade, Y., Lin, W.-H., Cong, J., & Wille, R.. (2025). Routing-Aware Placement for Zoned Neutral Atom-based Quantum Computing. In 2025 IEEE/ACM International Conference On Computer Aided Design (ICCAD) (pp. 1–9). IEEE. https://doi.org/10.1109/iccad66269.2025.11240721
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Smart Alerting: A Forecasting and Anomaly Detection System for Data-Driven Decision-Making
Luftensteiner, S., Schrammel, J., Diamond, L., & Degenfellner, R.. (2026). Smart Alerting: A Forecasting and Anomaly Detection System for Data-Driven Decision-Making. In Procedia Computer Science (pp. 376–383). Elsevier BV. https://doi.org/10.1016/j.procs.2026.02.079
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Streamlining AI Model Development and Evaluation in Industrial Settings by means of an Application
Luftensteiner, S., Schrammel, J., Diamond, L., & Degenfellner, R.. (2026). Streamlining AI Model Development and Evaluation in Industrial Settings by means of an Application. In Procedia Computer Science (pp. 3771–3780). Elsevier BV. https://doi.org/10.1016/j.procs.2026.02.412
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STRIPID: Simulation Test Ranking and Interactive Performance Inspection for PID controllers
Duque-Torres, A., Klammer, C., & Fischer, S.. (2025). STRIPID: Simulation Test Ranking and Interactive Performance Inspection for PID Controllers. In Lecture Notes in Computer Science (pp. 136–150). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-12092-2_9
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TEPHRA: Principled Discovery of Fuzzer Limitations
Sarafov, V., Markvica, D., & Brunthaler, S.. (2025). Tephra: Principled Discovery of Fuzzer Limitations. In 2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE) (pp. 2733–2745). IEEE. https://doi.org/10.1109/ase63991.2025.00224
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The Challenge of Generating and Evolving Real-Life Like Synthetic Test Data Without Accessing Real-World Raw Data - A Systematic Review
Tammisto, M., Shah, F. A., Rodriguez, D., & Pfahl, D.. (2025). The Challenge of Generating and Evolving Real‐Life Like Synthetic Test Data Without Accessing Real‐World Raw Data—A Systematic Review. In Expert Systems (p. None). Wiley. https://doi.org/10.1111/exsy.70164
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Unsupervised pre-processing selection method for improved model generalization applied to bioprocess spectral calibration models
Umprecht, A., Fonseca Diaz, V., Hüpfl, B., Kozma, B., Schwaighofer, A., Henson, M., Nikzad-Langerodi, R., & Spadiut, O. (2025). Unsupervised optimization of spectral pre-processing selection to achieve transfer of Raman calibration models. Measurement, 255, 117906.
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An Agentic Framework for Rapid Deployment of Edge AI Solutions in Industry 5.0
Martinez-Gil, J., Pichler, M., Bountouni, N., Koussouris, S., Barreiro, M. M., & Gusmeroli, S.. (2025). An Agentic Framework for Rapid Deployment of Edge AI Solutions in Industry 5.0. In IFIP Advances in Information and Communication Technology (pp. 55–68). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-05681-8_4
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Cloning Instruments, Model Maintenance and Calibration Transfer
Roger, J.-M., Diaz, V. F., & Nikzad-Langerodi, R. (2025). Cloning instruments, model maintenance and calibration transfer. TrAC Trends in Analytical Chemistry, 191, 118319.
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Fuzzing-based Grammar Inference for Context-free Languages
Sochor, Hannes. (2025). Fuzzing-based Grammar Inference for Context-free Languages. PhD Thesis, Johannes Kepler University Linz
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Graph-Oriented Layout Design for Field-Coupled Nanocomputing via Parallel Multi-Objective Search Space Exploration
Hofmann, S., Walter, M., & Wille, R.. (2025). Graph-Oriented Layout Design for Field-Coupled Nanocomputing via Parallel Multi-Objective Search Space Exploration. In IEEE Transactions on Circuits and Systems I: Regular Papers (pp. 1–14). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/tcsi.2025.3614709
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Human Perception for Print Defect Detection
Brunner, L., Pönitz, T., & Kromp, F.. (2026). Human perception for print defect detection. In Eighteenth International Conference on Machine Vision (ICMV 2025) (p. 81). SPIE. https://doi.org/10.1117/12.3096940
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LLM-Based Generation of Low-Code Development Platforms
Schenkenfelder, B. (2025). LLM-Based Generation of Low-Code Development Platforms. 28th International Conference on Model Driven Engineering Languages and Systems (MODELS). https://doi.org/10.1109/MODELS-C68889.2025.00015
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(epsilon, delta)-differentially private partial least squares regression
Nikzad-Langerodi, R., Kumar, M., Duy, D. N., & Alghasi, M. (2025). (ε,δ)-differentially private partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 264, 105465.
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AI4Green: A Framework for AI-based Resource Optimizations for Reliable Applications
Höfig, K., Döller, M., Waheed, F., Riß, F., Scholz, M., Bauer, J., Waclawek, H., Schäfer, G., Huber, S., Heinzl, B., Hellwig, M., & Finck, S.. (2025). AI4Green: A Framework for AI-Based Resource Optimizations for Reliable Applications. In Lecture Notes in Computer Science (pp. 321–332). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-05073-1_21
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Design and Development of a Conceptual System for Vertical Federated Learning Inspired by Multivariate Statistical Process Control
Mathab Alghasi (2025): Design and Development of a Conceptual System for Vertical Federated Learning Inspired by Multivariate Statistical Process Control. Master Thesis, Università di Catania
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Detecting and Cleaning Errors in Personal Contact Information with Large Language Models
Glock, A. C., Dominka-Kiss, C., Korom, P., & Ehrlinger, L. Detecting and Cleaning Errors in Personal Contact Information with Large Language Models. Proceedings of the VLDB Endowment. ISSN, 2150, 8097.
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Event-Based ADCs vs. Nyquist ADCs: Rethinking Performance Metrics
Dorrer, S., Werzi, A., Moser, B. A., Lunglmayr, M., & Pretl, H.. (2025). Event-Based ADCs vs. Nyquist ADCs: Rethinking Performance Metrics. In 2025 Austrochip Workshop on Microelectronics (Austrochip) (pp. 37–40). IEEE. https://doi.org/10.1109/austrochip67945.2025.11183710
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Flexible Variability Mining for IEC 61499 Control Software Applications with Varflix
Stummer, A., Hager, A.-L., & Rabiser, R.. (2025). Flexible Variability Mining for IEC 61499 Control Software Applications with Varflix. In Proceedings of the 29th ACM International Systems and Software Product Line Conference - Volume B (pp. 57–65). ACM. https://doi.org/10.1145/3748269.3749379
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Inferring Attributed Grammars from Parser Implementations
Pointner, A., Pichler, J., & Prähofer, H.. (2025). Inferring Attributed Grammars from Parser Implementations. In 2025 IEEE International Conference on Software Maintenance and Evolution (ICSME) (pp. 785–790). IEEE. https://doi.org/10.1109/icsme64153.2025.00080
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Localized statistics decoding for quantum low-density parity-check codes
Hillmann, T., Berent, L., Quintavalle, A. O., Eisert, J., Wille, R., & Roffe, J.. (2025). Localized statistics decoding for quantum low-density parity-check codes. In Nature Communications (p. None). Springer Science and Business Media LLC. https://doi.org/10.1038/s41467-025-63214-7
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MiNeuron: Minimal Neuron Realization for fast FPGA SNN Inference using Logic Optimization
Windhager, D., Ratschbacher, L., Moser, B. A., & Lunglmayr, M.. (2025). Mineuron: Minimal Neuron Realization For Fast Fpga Snn Inference Using Logic Optimization. In 2025 IEEE International Conference on Image Processing Workshops (ICIPW) (pp. 1–6). IEEE. https://doi.org/10.1109/icipw68931.2025.11385869
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QuickCell: Fast Automatic Design of Standard Cells for Silicon Dangling Bond Logic
Drewniok, J., Walter, M., Ng, S. S. H., Walus, K., & Wille, R.. (2025). <i>QuickCell</i>: Fast Automatic Design of Standard Cells for Silicon Dangling Bond Logic. In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (pp. 1–1). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/tcad.2025.3605537
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Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned
Schweighofer, K., Brune, B., Gruber, L., Schmid, S., Aufreiter, A., Gruber, A., Doms, T., Eder, S., Mayer, F., Stadlbauer, X.-P., Schwald, C., Zellinger, W., Nessler, B., & Hochreiter, S.. (2025). Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned. In None (p. None). arXiv. https://doi.org/10.48550/ARXIV.2509.08852
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Surrogate Modeling for Explainable Predictive Time Series Corrections
López, A., & Sobieczky, F.. (2026). Surrogate Modeling for Explainable Predictive Time Series Corrections. In Quality and Reliability Engineering International (p. None). Wiley. https://doi.org/10.1002/qre.70300
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Vision-Language Model for describing and segmenting Blastocysts
Neu, N. (2025). Vision-Language Model for describing and segmenting Blastocysts. Master Thesis, University of Applied Sciences Upper Austria, Hagenberg
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Automatically Refining Assertions for Efficient Debugging of Quantum Programs
Rovara, D., Burgholzer, L., & Wille, R.. (2025). Automatically Refining Assertions for Efficient Debugging of Quantum Programs. In 2025 IEEE International Conference on Quantum Computing and Engineering (QCE) (pp. 766–772). IEEE. https://doi.org/10.1109/qce65121.2025.00088
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Collaborative Trustworthy Foundation Model Framework: An Environmental Sustainability Use-Case to Detect Contamination Objects in Organic Waste Streams
Valentinitsch, A., Bencik, B., Brucker, M., Lammer, G., Adami, C., Kumar, M., Fischer, L., & Kromp, F.. (2025). Collaborative Trustworthy Foundation Model Framework: An Environmental Sustainability Use-Case to Detect Contamination Objects in Organic Waste Streams. In Communications in Computer and Information Science (pp. 30–44). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-02003-1_3
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Database and Expert Systems Applications - DEXA 2025 Workshops
Database and Expert Systems Applications - DEXA 2025 Workshops. (2026). Database and Expert Systems Applications - DEXA 2025 Workshops. In Communications in Computer and Information Science (p. None). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-02003-1
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Enhancing Training Efficiency of Physics-Informed Neural Networks for CFD Simulations
Pham, P., Spandan, V., Servadei, L., & Wille, R.. (2025). Enhancing Training Efficiency of Physics-Informed Neural Networks for CFD Simulations. In Lecture Notes in Networks and Systems (pp. 3–17). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-94892-3_1
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Improving Hardware Requirements for Fault-Tolerant Quantum Computing by Optimizing Error Budget Distributions
Forster, T. V., Quetschlich, N., Soeken, M., & Wille, R.. (2025). Improving Hardware Requirements for Fault-Tolerant Quantum Computing by Optimizing Error Budget Distributions. In 2025 IEEE International Conference on Quantum Computing and Engineering (QCE) (pp. 681–687). IEEE. https://doi.org/10.1109/qce65121.2025.00079
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Lattice Surgery Compilation Beyond the Surface Code
Herzog, L. S., Berent, L., Kubica, A., & Wille, R.. (2025). Lattice Surgery Compilation Beyond the Surface Code. In 2025 IEEE International Conference on Quantum Computing and Engineering (QCE) (pp. 489–500). IEEE. https://doi.org/10.1109/qce65121.2025.00061
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Managing Control Software Variability in Cyber-Physical Production Systems: The V4rdiac Approach
Fadhlillah, H. S., Meixner, K., Greiner, S., Gutierrez, A. M., & Rabiser, R.. (2025). Managing Control Software Variability in Cyber-Physical Production Systems: The V4rdiac Approach. In Proceedings of the 29th ACM International Systems and Software Product Line Conference - Volume A (pp. 236–236). ACM. https://doi.org/10.1145/3744915.3748482
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Metamorphic testing for optimisation: A case study on PID controller tuning
Duque-Torres, A., Klammer, C., Fischer, S., Ramler, R., & Pfahl, D. (2025). Metamorphic testing for optimisation: A case study on PID controller tuning. Information and Software Technology, 188, 107872.
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Orchestrating Multi-Zone Shuttling in Trapped-Ion Quantum Computers
Schoenberger, D., & Wille, R.. (2025). Orchestrating Multi-Zone Shuttling in Trapped-Ion Quantum Computers. In 2025 IEEE International Conference on Quantum Computing and Engineering (QCE) (pp. 1069–1075). IEEE. https://doi.org/10.1109/qce65121.2025.00119
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Quantum Circuit Optimization for the Fault-Tolerance Era: Do We Have to Start from Scratch?
Forster, T. V., Quetschlich, N., & Wille, R.. (2025). Quantum Circuit Optimization for the Fault-Tolerance Era: Do We Have to Start from Scratch?. In 2025 IEEE International Conference on Quantum Computing and Engineering (QCE) (pp. 584–590). IEEE. https://doi.org/10.1109/qce65121.2025.00070
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Quantum Entrepreneurship Lab: Training a Future Workforce for the Quantum Industry
Sander, A., Cercola, R., Capogrosso, A., Filipp, S., Jobst, B., Mendl, C. B., Pollmann, F., Trummer, C., Welpe, I., Werninghaus, M., Wille, R., & Wimmer, C.. (2025). Quantum Entrepreneurship Lab: Training a Future Workforce for the Quantum Industry. In 2025 IEEE International Conference on Quantum Computing and Engineering (QCE) (pp. 185–193). IEEE. https://doi.org/10.1109/qce65121.2025.20550
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REFLECTA: Reflection-based Scalable and Semantic Scripting Language Fuzzing
Zhang, C., Lee, G., Liu, Q., & Payer, M. (2025). REFLECTA: Reflection-based Scalable and Semantic Scripting Language Fuzzing. Proceedings of the 20th ACM Asia Conference on Computer and Communications Security, 1772–1787.
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The Missing Link: Joint Legal Citation Prediction Using Heterogeneous Graph Enrichment
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Third Tutorial on the Universal Variablity Language: Practical Extensions and Tool Ecosystem
Horcas, J. M., Sundermann, C., Grave, M., Galindo, J. A., Thüm, T., Rabiser, R., & Benavides, D.. (2025). Third Tutorial on the Universal Variablity Language: Practical Extensions and Tool Ecosystem. In Proceedings of the 29th ACM International Systems and Software Product Line Conference - Volume A (pp. 241–241). ACM. https://doi.org/10.1145/3744915.3749149
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A Framework for Debugging Quantum Programs
Rovara, D., Burgholzer, L., & Wille, R.. (2025). A Framework for Debugging Quantum Programs. In 2025 IEEE International Conference on Quantum Software (QSW) (pp. 130–136). IEEE. https://doi.org/10.1109/qsw67625.2025.00024
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A Fully Planar Approach to Field-coupled Nanocomputing: Scalable Placement and Routing Without Wire Crossings
Hien, B., Walter, M., Hofmann, S., & Wille, R.. (2025). A Fully Planar Approach to Field-Coupled Nanocomputing: Scalable Placement and Routing Without Wire Crossings. In 2025 IEEE 25th International Conference on Nanotechnology (NANO) (pp. 649–654). IEEE. https://doi.org/10.1109/nano63165.2025.11113822
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Building a Machine Learning Accelerator with Silicon Dangling Bonds: From Verilog to Quantum Dot Layout
Ng, S. S. H., Walter, M., Drewniok, J., Hofmann, S., Wille, R., & Walus, K.. (2025). Building a Machine Learning Accelerator with Silicon Dangling Bonds: From Verilog to Quantum Dot Layout. In 2025 IEEE 25th International Conference on Nanotechnology (NANO) (pp. 483–488). IEEE. https://doi.org/10.1109/nano63165.2025.11113747
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Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent
Kumar, M., Valentinitsch, A., Fuchs, M., Brucker, M., Bowles, J., Husakovic, A., Abbas, A., & Moser, B. A. (2025). Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent. Journal of Artificial Intelligence Research, 83.
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MNT Designer: A Comprehensive Design Tool for Field-Coupled Nanocomputing
Hofmann, S., Drewniok, J., Walter, M., & Wille, R.. (2025). MNT Designer: A Comprehensive Design Tool for Field-Coupled Nanocomputing. In 2025 IEEE 25th International Conference on Nanotechnology (NANO) (pp. 40–45). IEEE. https://doi.org/10.1109/nano63165.2025.11113823
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Shuttling for Trapped-Ion Quantum Computers with Embedded Processing Zones
Schoenberger, D., Hilder, J., Schmidt-Kaler, F., & Wille, R.. (2025). Shuttling for Trapped-Ion Quantum Computers with Embedded Processing Zones. In 2025 IEEE International Conference on Quantum Software (QSW) (pp. 123–129). IEEE. https://doi.org/10.1109/qsw67625.2025.00023
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The Operational Domain Explorer: A Comprehensive Framework to Unveil the Thermal Landscape of Silicon Dangling Bond Logic Beyond Conventional Operability
Walter, M., Drewniok, J., & Wille, R.. (2025). The Operational Domain Explorer: A Comprehensive Framework to Unveil the Thermal Landscape of Silicon Dangling Bond Logic Beyond Conventional Operability. In 2025 IEEE 25th International Conference on Nanotechnology (NANO) (pp. 28–33). IEEE. https://doi.org/10.1109/nano63165.2025.11113672
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A novel framework for systematic propositional formula simplification based on existential graphs
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Applying Mobility Detection and Prediction to Vehicular 5G Networks
Pargfrieder, Christoph. (2025). Applying Mobility Detection and Prediction to Vehicular 5G Networks. Master Thesis, Johannes Kepler University Linz. https://epub.jku.at/obvulihs/content/titleinfo/12067780
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Assembly Workers as PLC Programmers: A Low-Code Development Platform for Engine Manufacturing
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Assembly Workers as PLC Programmers: What End Users Need to Understand about Low-Code Development Platforms
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Assessing the strength of Metamorphic Testing applied to optimisation software—Experience from industry
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Behavioural Theory of Reflective Parallel Algorithms
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Design tasks and their complexity for the European Train Control System with Hybrid Train Detection
Engels, S., Peham, T., Przigoda, J., Przigoda, N., & Wille, R.. (2025). Design tasks and their complexity for the European Train Control System with Hybrid Train Detection. In EURO Journal on Transportation and Logistics (p. 100161). Elsevier BV. https://doi.org/10.1016/j.ejtl.2025.100161
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Dynamic Adaptation of Classification and Segmentation Models for Evolving Steel Scrap Classes Using Contrastive Learning
Preining, J. (2025). Dynamic Adaptation of Classification and Segmentation Models for Evolving Steel Scrap Classes Using Contrastive Learning. Master Thesis, University of Applied Sciences Upper Austria, Hagenberg
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Equivalence checking of quantum circuits via intermediary matrix product operator
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In-Situ Visual Programming
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Joint Cutting for Hybrid Schrödinger-Feynman Simulation of Quantum Circuits
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MendelFuzz: The Return of the Deterministic Stage
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Quantum Table: A Tangible Quantum Circuit Demonstrator
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Uncovering and Exploring the Intersection of Low-Code Development and Sustainability
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A Hardware Architecture for Efficient Adaptive Threshold-Based Sampling using Weyl’s Discrepancy
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A Survey on the Functionalities of Data Catalog Tools
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Advanced Detection of Source Code Clones via an Ensemble of Unsupervised Similarity Measures
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Automated Synthesis of Fault-Tolerant State Preparation Circuits for Quantum Error-Correction Codes
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Automating Invariant Filtering: Leveraging LLMs to Streamline Test Oracle Generation
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Balancing Software Innovation and Regulatory Compliance: Proceedings of the 17th International Conference on Software Quality, SWQD 2025
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Contemporary Software Modernization: Strategies, Driving Forces, and Research Opportunities
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Live Demonstration: An Application for Layout Resilience Analysis of Silicon Dangling Bond Logic
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On Tessellations of ReLU Neural Networks
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QuickTrace: An Efficient Contour Tracing Algorithm for Defect Robustness Simulation of Silicon Dangling Bond Logic
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Spiking Neural Network Accelerator Architecture for Differential-Time Representation using Learned Encoding
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Explainable Classification by Local Error Amplification
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Icewafl: A Configurable Data Stream Polluter
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Influence of Spike Encoding, Neuron Models and Quantization on SNN Performance
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MQT Core: The Backbone of the Munich Quantum Toolkit (MQT)
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RAM: Retrieval Augmented Modelling for Tabular In-Context Few-Shot Domain Adaptation
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Towards a flexible approach for understanding and comparing traces
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Unit Testing Past vs. Present - Examining LLMs' Impact on Defect Detection and Efficiency
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VFLBench: A Practical Benchmark for Vertical Federated Learning in Manufacturing
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An Abstract Simulator for Species Concentrations in Channel-Based Microfluidic Devices
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Bias by Design: Diversity Quantification to Mitigate Structural Bias Effects in AIG Logic Optimization
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Deterministic Fault-Tolerant State Preparation for Near-Term Quantum Error Correction: Automatic Synthesis Using Boolean Satisfiability
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Efficient and Scalable Post-Layout Optimization for Field-coupled Nanotechnologies
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Late Breaking Results: Physical Co-Design for Field-Coupled Nanocomputing
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On the sampling sparsity of analog-to-spike conversion based on leaky integrate-and-fire
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Optimal State Preparation for Logical Arrays on Zoned Neutral Atom Quantum Computers
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Personalized ML-Assisted Respiratory Muscle Training for Patients with Paraplegia
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Towards Fast Automatic Design of Silicon Dangling Bond Logic
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Automated Knowledge Graph Learning in Industrial Processes
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Efficient Cartesian Genetic Programming-Based Automatic Synthesis Framework for Reversible Quantum-Flux-Parametron Logic Circuits
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Forward and Backward Constrained Bisimulations for Quantum Circuits Using Decision Diagrams
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Leveraging Rowhammer for Physically Unique and Non-tamperable Device Identification
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Physical Design for Field-coupled Nanocomputing with Discretionary Cost Objectives
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Dynamic Time Warping for Classifying Long-Term Trends in Time Series
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MQT Predictor: Automatic Device Selection with Device-Specific Circuit Compilation for Quantum Computing
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An overview of civic engagement tools for rural communities
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Augmenting the Interpretability of GraphCodeBERT for Code Similarity Tasks
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Dynamic Knowledge Graph-based Measurement of Data Quality
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Extensible and Robust Evaluation of Similarity Queries
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Investigating the Potential of Latent Space for the Classification of Paint Defects
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MTD-DS: an SLA-aware Decision Support Benchmark for Multi-tenant Parallel DBMSs
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On Space Folds of ReLU Neural Networks
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Enhancing and Personalising Endometriosis Care with Causal Machine Learning
Hine, A., Webber, T., & Bowles, J.. (2024). Enhancing and Personalising Endometriosis Care with Causal Machine Learning. In Lecture Notes in Networks and Systems (pp. 3–25). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-74443-3_1
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Evaluating AI-based Code Segmentation for ABAP Programs in an Industrial Use Case
Mayer, R., Moser, M., Greif, N., Schnitzhofer, F., Geist, V., & Pinzger, M. (2024). Evaluating AI-Based Code Segmentation for ABAP Programs in an Industrial Use Case. Product-Focused Software Process Improvement. Industry-, Workshop-, and Doctoral Symposium Papers, 131–147.
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On-farm NIR sensor for milk analysis: exploitation of bias monitoring and bias correction
van Nuenen, A., Fonseca Diaz, V., Diaz-Olivares, J. A., Saeys, W., & Aernouts, B. (2024). On-farm NIR sensor for milk analysis: Exploitation of bias monitoring and bias correction. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 320, 124544.
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Responsible Annotation - Von der Idee zur Praxis: Inklusives Team markiert Daten für KI-Training
Schenkenfelder, B., Brandstätter, U., Fischer, L., Ramler, R., Laister, D., Hartl, M., & Wurm, M. (2024). Responsible Annotation - Von der Idee zur Praxis: Inklusives Team markiert Daten für KI-Training. BI-Spektrum 5/2024.
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Shuttling for Scalable Trapped-Ion Quantum Computers
Schoenberger, D., Hillmich, S., Brandl, M., & Wille, R. (2024). Shuttling for Scalable Trapped-Ion Quantum Computers. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 1–1.
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The impact of new package managers on the library dependency ecosystem
Rahkema, K., Pfahl, D., & Ramler, R. (2024). The impact of new package managers on the library dependency ecosystem. PeerJ Computer Science, 10, e2617. Portico.
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Towards Solving Short-Term Generation Scheduling Problems on Quantum Computers
Bruckner, S., Ferrarotti, F., Ramler, R., Wille, R., & Hillmich, S. (2024). Towards Solving Short-Term Generation Scheduling Problems on Quantum Computers. Product-Focused Software Process Improvement. Industry-, Workshop-, and Doctoral Symposium Papers, 164–170.
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Understanding Microservice Runtime Monitoring Data for Anomaly Detection with Structural Equation Modeling
Steidl, M., Leitner, M., Urbanke, P., Gattringer, M., Felderer, M., Ristov, S. (2025). Understanding Microservice Runtime Monitoring Data for Anomaly Detection with Structural Equation Modeling. Product-Focused Software Process Improvement. PROFES 2024. Lecture Notes in Computer Science, vol 15452.
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Verification of Quantum Circuits
Wille, R., & Burgholzer, L.. (2024). Verification of Quantum Circuits. In Handbook of Computer Architecture (pp. 1413–1440). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-9314-3_43
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Automated Design for Multiorgan-on-Chip Geometries
Emmerich, M., Ebner, P., & Wille, R.. (2025). Automated Design for Multiorgan-on-Chip Geometries. In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (pp. 2287–2299). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/tcad.2024.3509795
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Generating and Evolving Real-Life Like Synthetic Data for e-Government Services Without Using Real-World Raw Data
Tammisto, M.-A., Pfahl, D., & Shah, F. A.. (2024). Generating and Evolving Real-Life Like Synthetic Data for e-Government Services Without Using Real-World Raw Data. In Lecture Notes in Computer Science (pp. 173–178). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-78392-0_12
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GrammarForge: Learning Program Input Grammars for Fuzz Testing
Sochor, H., Ferrarotti, F., & Wille, R. (2024). GrammarForge: Learning Program Input Grammars for Fuzz Testing. Software Engineering and Formal Methods, 272–289.
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Hybrid Circuit Mapping: Leveraging the Full Spectrum of Computational Capabilities of Neutral Atom Quantum Computers
Schmid, L., Park, S., & Wille, R. (2024). Hybrid Circuit Mapping: Leveraging the Full Spectrum of Computational Capabilities of Neutral Atom Quantum Computers. Proceedings of the 61st ACM/IEEE Design Automation Conference, 1–6.
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Managing Human-AI Collaborations within Industry 5.0 Scenarios via Knowledge Graphs: Key Challenges and Lessons Learned
Krause, F., Paulheim, H., Kiesling, E., Kurniawan, K., Leva, M. C., Estrada-Lugo, H. D., Stübl, G., Üre, N. K., Dominguez-Ledo, J., Khan, M., Demolder, P., Gaux, H., Heinzl, B., Hoch, T., Martinez-Gil, J., Silvina, A., & Moser, B. A. (2024). Managing human-AI collaborations within Industry 5.0 scenarios via knowledge graphs: key challenges and lessons learned. Frontiers in Artificial Intelligence, 7.
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Mixed-Dimensional Qudit State Preparation Using Edge-Weighted Decision Diagrams
Mato, K., Hillmich, S., & Wille, R. (2024). Mixed-Dimensional Qudit State Preparation Using Edge-Weighted Decision Diagrams. Proceedings of the 61st ACM/IEEE Design Automation Conference, 1–6.
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Modular and extendable 1D-simulation for microfluidic devices
Emmerich, M., Costamoling, F., & Wille, R.. (2024). Modular and extendable 1D-simulation for microfluidic devices. In Scientific Reports (p. None). Springer Science and Business Media LLC. https://doi.org/10.1038/s41598-024-77741-8
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Noise-Aware Quantum Circuit Simulation with Decision Diagrams
Grurl, T., Fuß, J., & Wille, R.. (2025). Noise-Aware Quantum Circuit Simulation with Decision Diagrams. In Synthesis Lectures on Engineering, Science, and Technology (p. None). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-71036-0
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Constraint-based Measurement and Aggregation of Data Quality
Schrott, J. (2024). Constraint-based Measurement and Aggregation of Data Quality. Master Thesis, Johannes Kepler University Linz.
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Contemporary Software Modernization: Strategies, Driving Forces, and Research Opportunities - Supplementary Material [Data set]
Guez Assunção, W. K., Marchezan, L., Arkoh, L., Egyed, A., & Ramler, R.. (2024). Contemporary Software Modernization: Strategies, Driving Forces, and Research Opportunities - Supplementary Material [Data set]. In None (p. None). Zenodo. https://doi.org/10.5281/ZENODO.13866355
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Contributions to Systems Software and Service Process Improvement and Innovation Based on Recent Advances
Colomo‐Palacios, R., Messnarz, R., & Biró, M. (2024). Contributions to Systems Software and Service Process Improvement and Innovation Based on Recent Advances. Journal of Software: Evolution and Process, 37(1). Portico.
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Decoding quantum color codes with MaxSAT
Berent, L., Burgholzer, L., Derks, P.-J. H. S., Eisert, J., & Wille, R.. (2024). Decoding quantum color codes with MaxSAT. In Quantum (p. 1506). Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften. https://doi.org/10.22331/q-2024-10-23-1506
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Evaluation of Code Similarity Search Strategies in Large-Scale Codebases
Martinez-Gil, J., & Yin, S. (2024). Evaluation of Code Similarity Search Strategies in Large-Scale Codebases. Transactions on Large-Scale Data- and Knowledge-Centered Systems LVII, 99–113.
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Integrate-and-Fire from a Mathematical and Signal Processing Perspective
Moser, B. A., Werzi, A., & Lunglmayr, M.. (2024). Integrate-and-Fire from a Mathematical and Signal Processing Perspective. In 2024 58th Asilomar Conference on Signals, Systems, and Computers (pp. 567–571). IEEE. https://doi.org/10.1109/ieeeconf60004.2024.10942672
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Leveraging the Power of LLMs to Transform Robot Programs into Low-Code
Schenkenfelder, B., Salomon, C., Schwandtner, M., Zefferer, R., Derfler, M., & Wimmer, M. (2024). Leveraging the Power of LLMs to Transform Robot Programs into Low-Code. 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA), 1–4.
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Low-Code Development and End-User Development: (How) Are They Different?
Schenkenfelder, B., Brandstätter, U., Kirchtag, H., & Wimmer, M. (2024). Low-Code Development and End-User Development: (How) Are They Different? Proceedings of the First International Workshop on Participatory Design & End-User Development - Building Bridges, co-located with the International Nordic Conference on Human-Computer Interaction (NordiCHI 2024).
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On the Robustness of Out-of-Distribution Detection Methods for Camera-based Systems
Huber, C., Lehner, B., Hofmann, C., Moser, B., & Feger, R.. (2024). On the Robustness of Out-of-Distribution Detection Methods for Camera-based Systems. In 2024 58th Asilomar Conference on Signals, Systems, and Computers (pp. 367–371). IEEE. https://doi.org/10.1109/ieeeconf60004.2024.10943036
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The Turing Game
Lewandowski, M., Schmid, S. L., Mederitsch, P., Aufreiter, A., Aichinger, G., Nessler, F., Bergsmann, S., Szolga, V., Halmdienst, T., & Nessler, B. (2024). The Turing Game. In The First Workshop on System-2 Reasoning at Scale, NeurIPS'24. Retrieved from https://openreview.net/forum?id=YiquAWqFw3
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Towards an Optimization Pipeline for the Design of Train Control Systems with Hybrid Train Detection
Engels, S., & Wille, R. (2024). <i>Towards an Optimization Pipeline for the Design of Train Control Systems with Hybrid Train Detection (Short Paper)</i>. Schloss Dagstuhl – Leibniz-Zentrum für Informatik. https://doi.org/10.4230/OASICS.ATMOS.2024.12
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A Predictive Approach for Selecting the Best Quantum Solver for an Optimization Problem
Volpe, D., Quetschlich, N., Graziano, M., Turvani, G., & Wille, R. (2024). A Predictive Approach for Selecting the Best Quantum Solver for an Optimization Problem. 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 1014–1025.
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An Abstract Model and Efficient Routing for Logical Entangling Gates on Zoned Neutral Atom Architectures
Stade, Y., Schmid, L., Burgholzer, L., & Wille, R. (2024). An Abstract Model and Efficient Routing for Logical Entangling Gates on Zoned Neutral Atom Architectures. 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 784–795.
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Analyzing Operator States and the Impact of AI-Enhanced Decision Support in Control Rooms: A Human-in-the-Loop Specialized Reinforcement Learning Framework for Intervention Strategies
Abbas, A. N., Amazu, C. W., Mietkiewicz, J., Briwa, H., Perez, A. A., Baldissone, G., … Leva, M. C. (2024). Analyzing Operator States and the Impact of AI-Enhanced Decision Support in Control Rooms: A Human-in-the-Loop Specialized Reinforcement Learning Framework for Intervention Strategies. International Journal of Human–Computer Interaction, 1–35. https://doi.org/10.1080/10447318.2024.2391605
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Automatic Validation and Design of Microfluidic Devices Following the ISO 22916 Standard
Ebner, P., & Wille, R. (2024). Automatic Validation and Design of Microfluidic Devices Following the ISO 22916 Standard. 2024 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 278–283.
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Breaking Boundaries in Industrial Programming: Towards a Novel Architecture for Machine Controls
Wetzlmaier, T., Fischer, S., Wöß, A., Löberbauer, M., Koll, G., & Fischer, F. (2024). Breaking Boundaries in Industrial Programming: Towards a Novel Architecture for Machine Controls. 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA), 1–4.
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CertGraph: Towards a Comprehensive Knowledge Graph for Cloud Security Certifications
Schöberl, S., Banse, C., Geist, V., Kunz, I., & Pinzger, M. (2024). CertGraph: Towards a Comprehensive Knowledge Graph for Cloud Security Certifications. Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, 76–77.
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Comparing Lazy Constraint Selection Strategies in Train Routing with Moving Block Control
Engels, S., & Wille, R. (2024). Comparing Lazy Constraint Selection Strategies in Train Routing with Moving Block Control. Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS), 39, 585–590.
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Energy-based Hopfield Boosting for Out-of-Distribution Detection
Hochreiter, S., Hofmann, C., Klotz, D., Lehner, B., & Schmid, S.. (2024). Energy-based Hopfield Boosting for Out-of-Distribution Detection. In Advances in Neural Information Processing Systems 37 (pp. 131859–131919). Neural Information Processing Systems Foundation, Inc. (NeurIPS). https://doi.org/10.52202/079017-4192
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Enhancing Reaction Systems with Guards for Analysing Comorbidity Treatment Strategies
Bowles, J., Brodo, L., Bruni, R., Falaschi, M., Gori, R., & Milazzo, P. (2024). Enhancing Reaction Systems with Guards for Analysing Comorbidity Treatment Strategies. Computational Methods in Systems Biology, 27–44.
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First Experiments on Automated Execution of Gherkin Test Specifications with Collaborating LLM Agents
Bergsmann, S., Schmidt, A., Fischer, S., & Ramler, R. (2024). First Experiments on Automated Execution of Gherkin Test Specifications with Collaborating LLM Agents. Proceedings of the 15th ACM International Workshop on Automating Test Case Design, Selection and Evaluation, 12–15.
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Load Shifting in Energy Communities by Providing User-Centered Recommendations - Forecast, Optimization and Potential
Gaisberger, L., Chasparis, G. C., & Traunmüller, W. (2024). Load Shifting in Energy Communities by Providing User-Centered Recommendations – Forecast, Optimization and Potential. 41st European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC 2024).
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QDMI - Quantum Device Management Interface: Hardware-Software Interface for the Munich Quantum Software Stack
Wille, R., Schmid, L., Stade, Y., Echavarria, J., Schulz, M., Schulz, L., & Burgholzer, L. (2024). QDMI - Quantum Device Management Interface: Hardware-Software Interface for the Munich Quantum Software Stack. 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 573–574.
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Technology Mapping for Cryogenic CMOS Circuits
Hien, B., Walter, M., van Santen, V. M., Klemme, F., Parihar, S. S., Pahwa, G., Chauhan, Y. S., Amrouch, H., & Wille, R. (2024). Technology Mapping for Cryogenic CMOS Circuits. 2024 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 272–277.
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Towards Equivalence Checking of Classical Circuits Using Quantum Computing
Quetschlich, N., Forster, T. V., Osterwind, A., Helms, D., & Wille, R. (2024). Towards Equivalence Checking of Classical Circuits Using Quantum Computing. 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 268–274.
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Understanding and Improving Coverage Tracking with AFL++ (Registered Report)
Sarafov, V., Markvica, D., Berlakovich, F., Bernad, M., & Brunthaler, S.. (2024). Understanding and Improving Coverage Tracking with AFL++ (Registered Report). In Proceedings of the 3rd ACM International Fuzzing Workshop (pp. 80–89). ACM. https://doi.org/10.1145/3678722.3685537
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Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators
Alkin, B., Brandstetter, J., Fürst, A., Gruber, L., Holzleitner, M., & Schmid, S.. (2024). Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators. In Advances in Neural Information Processing Systems 37 (pp. 25152–25194). Neural Information Processing Systems Foundation, Inc. (NeurIPS). https://doi.org/10.52202/079017-0793
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Using Compiler Frameworks for the Evaluation of Hardware Design Choices in Trapped-Ion Quantum Computers
Schoenberger, D., Hillmich, S., Brand, M., & Wille, R. (2024). Using Compiler Frameworks for the Evaluation of Hardware Design Choices in Trapped-Ion Quantum Computers. 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 1102–1108.
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Utilizing Resource Estimation for the Development of Quantum Computing Applications
Quetschlich, N., Soeken, M., Murali, P., & Wille, R. (2024). Utilizing Resource Estimation for the Development of Quantum Computing Applications. 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 232–238.
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A Framework for the Design and Realization of Alternative Superconducting Quantum Architectures
Kunasaikaran, J., Mato, K., & Wille, R. (2024). A Framework for the Design and Realization of Alternative Superconducting Quantum Architectures. 2024 IEEE 54th International Symposium on Multiple-Valued Logic (ISMVL), 91–96.
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Challenges for Quantum Software Engineering: An Industrial Application Scenario Perspective
Carbonelli, C., Felderer, M., Jung, M., Lobe, E., Lochau, M., Luber, S., Mauerer, W., Ramler, R., Schaefer, I., & Schroth, C. (2024). Challenges for Quantum Software Engineering: An Industrial Application Scenario Perspective. Quantum Software, 311–335.
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Database and Expert Systems Applications - DEXA 2024 Workshops
Database and Expert Systems Applications - DEXA 2024 Workshops. (2024). In B. Moser, L. Fischer, A. Mashkoor, J. Sametinger, A.-C. Glock, M. Mayr, & S. Luftensteiner (Eds.), Communications in Computer and Information Science. Springer Nature Switzerland.
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Dynamic Time Warping for Phase Recognition in Tribological Sensor Data
Glock, A.-C., & Fürnkranz, J.. (2024). Dynamic Time Warping for Phase Recognition in Tribological Sensor Data. In Lecture Notes in Computer Science (pp. 245–250). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-68323-7_20
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How Industry Tackles Anomalies during Runtime: Approaches and Key Monitoring Parameters
Steidl, M., Dornauer, B., Felderer, M., Ramler, R., Racasan, M.-C., & Gattringer, M. (2024). How Industry Tackles Anomalies during Runtime: Approaches and Key Monitoring Parameters. 2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 364–372.
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Knowledge Guided Clustering Medieval Polychromy
Sobieczky, F., & Sobieczky, E. (2024). Knowledge Guided Clustering Medieval Polychromy. Database and Expert Systems Applications - DEXA 2024 Workshops, 115–125.
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Learning Paradigms and Modelling Methodologies for Digital Twins in Process Industry
Mayr, M., Chasparis, G. C., & Küng, J. (2024). Learning Paradigms and Modelling Methodologies for Digital Twins in Process Industry. Big Data Analytics and Knowledge Discovery, 34–47.
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Multi-controlled Phase Gate Synthesis with ZX-calculus applied to Neutral Atom Hardware
Staudacher, K., Schmid, L., Zeiher, J., Wille, R., & Kranzlmüller, D. (2024). Multi-controlled Phase Gate Synthesis with ZX-calculus applied to Neutral Atom Hardware. Electronic Proceedings in Theoretical Computer Science, 406, 96–116.
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NADA: NMF-based Anomaly Detection in Adjacency-Matrices for Industrial Machine Log-files
Luftensteiner, S., Praher, P., & Schwarz, N. (2024). NADA: NMF-Based Anomaly Detection in Adjacency-Matrices for Industrial Machine Log-Files. Big Data Analytics and Knowledge Discovery, 369–374.
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On the Solvability of the XOR Problem by Spiking Neural Networks
Moser, B. A., & Lunglmayr, M. (2024). On the Solvability of the XOR Problem by Spiking Neural Networks. Database and Expert Systems Applications - DEXA 2024 Workshops, 57–66.
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Replication Package: Anomaly detection via runtime monitoring data for structural equation modeling
Steidl, M., Leitner, M., Urbanke, P., Gattringer, M., Felderer, M., & Ristov, S.. (2024). Replication Package: Anomaly detection via runtime monitoring data for structural equation modeling [Data set]. In None (p. None). Zenodo. https://doi.org/10.5281/ZENODO.13324135
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Risk Assessment in AI System Engineering: Experiences and Lessons Learned from a Practitioner’s Perspective
Fuchs, M., Fischer, L., Montuoro, A., Kumar, M., & Moser, B. A. (2024). Risk Assessment in AI System Engineering: Experiences and Lessons Learned from a Practitioner’s Perspective. Database and Expert Systems Applications - DEXA 2024 Workshops, 67–76.
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Stripping Quantum Decision Diagrams of their Identity
Sander, A., Florea, I.-A., Burgholzer, L., & Wille, R. (2024). Stripping Quantum Decision Diagrams of their Identity. 2024 IEEE International Conference on Quantum Software (QSW), 168–174.
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Supervised and penalized baseline correction
Erik Andries, Ramin Nikzad-Langerodi, Supervised and penalized baseline correction, Chemometrics and Intelligent Laboratory Systems, 2024,105200, ISSN 0169-7439, https://doi.org/10.1016/j.chemolab.2024.105200.
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The Metamorphic Lighthouse: Understanding the Input Data Space of Metamorphic Relations
Duque-Torres, A., Pfahl, D., Klammer, C., Fischer, S., & Ramler, R. (2024). The Metamorphic Lighthouse: Understanding the Input Data Space of Metamorphic Relations. 2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 379–386.
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The MQT Handbook : A Summary of Design Automation Tools and Software for Quantum Computing
Wille, R., Berent, L., Forster, T., Kunasaikaran, J., Mato, K., Peham, T., Quetschlich, N., Rovara, D., Sander, A., Schmid, L., Schönberger, D., Stade, Y., & Burgholzer, L. (2024). The MQT Handbook : A Summary of Design Automation Tools and Software for Quantum Computing. 2024 IEEE International Conference on Quantum Software (QSW), 1–8.
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The Past, Present, and Future of Research on the Continuous Development of AI
Steidl, M., Ramler, R., & Felderer, M. (2024). The Past, Present, and Future of Research on the Continuous Development of AI. 2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 300–308.
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Towards an Automatic Framework for Solving Optimization Problems with Quantum Computers
Volpe, D., Quetschlich, N., Graziano, M., Turvani, G., & Wille, R. (2024). Towards an Automatic Framework for Solving Optimization Problems with Quantum Computers. 2024 IEEE International Conference on Quantum Software (QSW), 46–57.
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Towards Application-Aware Quantum Circuit Compilation
Quetschlich, N., Kiwit, F. J., Wolf, M. A., Riofrio, C. A., Burgholzer, L., Luckow, A., & Wille, R. (2024). Towards Application-Aware Quantum Circuit Compilation. 2024 IEEE International Conference on Quantum Software (QSW), 135–142.
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A Hierarchical Framework for Interpretable, Safe, and Specialized Deep Reinforcement Learning: Applications in Industrial Maintenance, Process Control, and Robotics
Abbas, A. (2024). A Hierarchical Framework for Interpretable, Safe, and Specialised Deep Reinforcement Learning. Technological University Dublin. https://doi.org/10.21427/P05P-AZ54
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Contemporary Software Modernization: Perspectives and Challenges to Deal with Legacy Systems
Assunção, Wesley KG, Luciano Marchezan, Alexander Egyed, and Rudolf Ramler (2024). Contemporary software modernization: Perspectives and challenges to deal with legacy systems. arXiv preprint arXiv:2407.04017 (2024).
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DQD: The Data Quality Definition Ontology
Schrott, J., Meindl, R., Lettner, C., Wöß, W., Ehrlinger, L. (2024). DQD: The Data Quality Definition Ontology. In: Garoufallou, E., Sartori, F. (eds) Metadata and Semantic Research. MTSR 2023. Communications in Computer and Information Science, vol 2048. Springer, Cham.
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Evaluation of literature reviews & primary sources thereof regarding the continuous development of AI
Steidl, M., Ramler, R., & Felderer, M.. (2024). Evaluation of literature reviews & primary sources thereof regarding the continuous development of AI [Data set]. In None (p. None). Zenodo. https://doi.org/10.5281/ZENODO.10173594
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Exploring the Influence of Human System Interfaces: Introducing Support Tools and an Experimental Study
Amazu, C. W., Mietkiewicz, J., Abbas, A. N., Briwa, H., Alonso-Perez, A., Baldissone, G., Fissore, D., Demichela, M., & Leva, M. C. (2024). Exploring the Influence of Human System Interfaces: Introducing Support Tools and an Experimental Study. International Journal of Human–Computer Interaction, 1–18.
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GlueZilla: Efficient and Scalable Software to Hardware Binding using Rowhammer
Mechelinck, R., Dorfmeister, D., Fischer, B., Volckaert, S., & Brunthaler, S. (2024). GlueZilla: Efficient and Scalable Software to Hardware Binding using Rowhammer. Lecture Notes in Computer Science, 416–438.
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Safety-Driven Deep Reinforcement Learning Framework for Cobots: A Sim2Real Approach
Abbas, A. N., Mehak, S., Chasparis, G. C., Kelleher, J. D., Guilfoyle, M., Leva, M. C., & Ramasubramanian, A. K. (2024). Safety-Driven Deep Reinforcement Learning Framework for Cobots: A Sim2Real Approach. 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT), 16, 2917–2923.
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SNN Architecture for Differential Time Encoding Using Decoupled Processing Time
Windhager, D., Moser, B. A., & Lunglmayr, M. (2024). SNN Architecture for Differential Time Encoding Using Decoupled Processing Time. 2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS).
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Spiking Neural Networks in the Alexiewicz Topology: A New Perspective on Analysis and Error Bounds
Moser, B. A., & Lunglmayr, M. (2024). Spiking neural networks in the Alexiewicz topology: A new perspective on analysis and error bounds. Neurocomputing, 128190.
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XentricAI: A Gesture Sensing Calibration Approach Through Explainable and User-Centric AI
Seifi, S., Sukianto, T., Strobel, M., Carbonelli, C., Servadei, L., & Wille, R. (2024). XentricAI: A Gesture Sensing Calibration Approach Through Explainable and User-Centric AI. Explainable Artificial Intelligence, 232–246.
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Design Considerations for a Multi-user General-purpose Flow-based Visual Programming Environment
Brandstätter, U., Schenkenfelder, B., Hohensinger, D., & Kirchtag, H. (2024). Design Considerations for a Multi-user General-purpose Flow-based Visual Programming Environment. Proceedings of the 2024 International Conference on Advanced Visual Interfaces.
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Lessons Learnt From Human-In-Loop Experimental Scenarios For Advanced Automation In Process Safety
C. W. Amazu, J. Mietkiewicz, A. N. Abbas, G. Baldissone, M. Demichela, D. Fissorea, & M. C. Leva, (2024). Lessons Learnt From Human-In-Loop Experimental Scenarios For Advanced Automation In Process Safety. Proceedings of the 34th European Safety and Reliability Conference (ESREL2024).
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MNT Bench: Benchmarking Software and Layout Libraries for Field-Coupled Nanocomputing
Hofmann, S., Walter, M., & Wille, R. (2024). MNT Bench: Benchmarking Software and Layout Libraries for Field-Coupled Nanocomputing. 2024 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 1–2.
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Modal Extensions of the Logic of Abstract State Machines
Ferrarotti, F., & Schewe, K.-D. (2024). Modal Extensions of the Logic of Abstract State Machines. Rigorous State-Based Methods, 123–140.
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Similarity-based client selection for mitigating privacy risks and data heterogeneity in federated learning
Fuchs, Magdalena. (2024). Similarity-based client selection for mitigating privacy risks and data heterogeneity in federated learning. Master Thesis, Technische Universität Graz. https://doi.org/10.3217/9ES6Z-RWR91
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Variational Bayesian Deep Fuzzy Models for Interpretable Classification
Kumar, M., Singh, S., & Bowles, J. (2024). Variational Bayesian deep fuzzy models for interpretable classification. Engineering Applications of Artificial Intelligence, 132, 107900.
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Water Demand Prediction utilising Graph Federated Learning
Brucker, M. (2024). Water Demand Prediction utilising Graph Federated Learning. Master Thesis, University of Applied Sciences Upper Austria, Hagenberg
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Controlled Local Surrogate Modeling for Classification
Sobieczky, F., Dudkin, E., & Zesinek, J. (2024). Learning the inhomogenous term of a linear ODE. Procedia Computer Science, 232, 1548–1553.
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A News Article Tag Categorization Ontology
Ehrlinger, L., Holzner, H., Hemelmayr, N., & Wöß, W. (2024). A News Article Tag Categorization Ontology. Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing.
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Atomic Defect-Aware Physical Design of Silicon Dangling Bond Logic on the H-Si(100)-2x1 Surface
Walter, M., Croshaw, J., Hang Ng, S. S., Walus, K., Wolkow, R., & Wille, R. (2024). Towards Atomic Defect-Aware Physical Design of Silicon Dangling Bond Logic on the H -Si $(100)-2\times 1$ Surface. 2024 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 1–2.
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Design Automation for Organs-on-Chip
Emmerich, M., Ebner, P., & Wille, R. (2024). Design Automation for Organs-on-Chip. 2024 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 1–6.
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P3LS: Partial Least Squares under privacy preservation
Nguyen Duy, D., & Nikzad-Langerodi, R. (2024). P3LS: Partial Least Squares under privacy preservation. Journal of Process Control, 138, 103229.
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Predictive change point detection for heterogeneous data
Glock, A.-C., Sobieczky, F., Fürnkranz, J., Filzmoser, P., & Jech, M. (2024). Predictive change point detection for heterogeneous data. Neural Computing and Applications.
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Replication Package: The Past, Present, and Future of Research on the Continuous Development of AI [Data Set]
Steidl, M., Ramler, R., & Felderer, M.. (2024). Replication Package: The Past, Present, and Future of Research on the Continuous Development of AI [Data set]. In None (p. None). Zenodo. https://doi.org/10.5281/ZENODO.8248724
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Towards Cycle-based Shuttling for Trapped-Ion Quantum Computers
Schoenberger, D., Hillmich, S., Brandl, M., & Wille, R. (2024). Towards Cycle-based Shuttling for Trapped-Ion Quantum Computers (Extended Abstract). 2024 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 1–2.
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Software Quality as a Foundation for Security: Proceedings of the 16th International Conference on Software Quality, SWQD 2024
Software Quality as a Foundation for Security. (2024). In P. Bludau, R. Ramler, D. Winkler, & J. Bergsmann (Eds.), Lecture Notes in Business Information Processing. Springer Nature Switzerland.
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A Complete Fragment of LTL(EB)
Ferrarotti, F., Rivière, P., Schewe, K.-D., Singh, N. K., & Ameur, Y. A. (2024). A Complete Fragment of LTL(EB). Foundations of Information and Knowledge Systems, 237–255.
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A PUF-Based Approach for Copy Protection of IP in Neural Network Models
Dorfmeister, D., Ferrarotti, F., Fischer, B., Schwandtner, M., & Sochor, H. (2024). A PUF-Based Approach for Copy Protection of Intellectual Property in Neural Network Models. Lecture Notes in Business Information Processing, 153–169.
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An Overview of Microservice-Based Systems Used for Evaluation in Testing and Monitoring: A Systematic Mapping Study
Fischer, S., Urbanke, P., Ramler, R., Steidl, M., & Felderer, M. (2024). An Overview of Microservice-Based Systems Used for Evaluation in Testing and Monitoring: A Systematic Mapping Study. Proceedings of the 5th ACM/IEEE International Conference on Automation of Software Test (AST 2024).
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Industrial Experience Report on AI-Assisted Coding in Professional Software Development
Ramler, R., Moser, M., Fischer, L., Nissl, M., & Heinzl, R. (2024). Industrial Experience Report on AI-Assisted Coding in Professional Software Development. Proceedings of the 1st International Workshop on Large Language Models for Code, 1–7.
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Responsible AI Engineering: The Case of an Inclusive Image Annotation Team in a Global Technology Company
Schenkenfelder, B., Brandstätter, U., Fischer, L., Ramler, R., Laister, D., Hartl, M., & Wurm, M. (2024). Responsible AI Engineering: The Case of an Inclusive Image Annotation Team in a Global Technology Company. Proceedings of the 2nd International Workshop on Responsible AI Engineering.
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Source Code Clone Detection Using Unsupervised Similarity Measures
Martinez-Gil, J. (2024). Source Code Clone Detection Using Unsupervised Similarity Measures. Lecture Notes in Business Information Processing, 21–37.
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Thinking Outside the Clock: Physical Design for Field-coupled Nanocomputing with Deep Reinforcement Learning
Hofmann, S., Walter, M., Servadei, L., & Wille, R. (2024). Thinking Outside the Clock: Physical Design for Field-coupled Nanocomputing with Deep Reinforcement Learning. 2024 25th International Symposium on Quality Electronic Design (ISQED), 1–8.
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Towards Integrating Knowledge Graphs into Process- Oriented Human-AI Collaboration in Industry
Heinzl, B., Silvina, A., Krause, F., Schwarz, N., Kurniawan, K., Kiesling, E., Pichler, M., & Moser, B. (2024). Towards Integrating Knowledge Graphs into Process-Oriented Human-AI Collaboration in Industry. Lecture Notes in Business Information Processing, 76–87.
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Variability debt in opportunistic reuse: A multi-project field study
Wolfart, D., Martinez, J., Assunção, W. K. G., Colanzi, T. E., & Egyed, A.. (2024). Variability debt in opportunistic reuse: A multi-project field study. In Journal of Systems and Software (p. 111969). Elsevier BV. https://doi.org/10.1016/j.jss.2024.111969
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Application domain definition for functional trustworthiness certification of AI
Schmid, S., Aufreiter, A., & Nessler, B.. (2025). Application domain definition for functional trustworthiness certification of AI. In None (p. None). innsbruck university press. https://doi.org/10.15203/99106-150-2-03
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Austrian Symposium on AI, Robotics, and Vision (AIRoV) Proceedings
Nessler, B., Piater, J., & Roth, P. M.. (2025). Austrian Symposium on AI, Robotics, and Vision (AIRoV) – Proceedings – March 26–27, 2024 (University of Innsbruck). In None (p. None). innsbruck university press. https://doi.org/10.15203/99106-150-2
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FedMSPC: A Federated Multivariate Statistical Process Control Framework For Privacy-preserving Process Modeling Across Company Borders
Nguyen Duy, D., Gabauer, D., & Nikzad-Langerodi, R. (2024). FedMSPC: A Federated Multivariate Statistical Process Control Framework For Privacy-Preserving Process Modeling Across Company Borders. Lecture Notes in Mechanical Engineering, 29–47.
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Fuzzing-based Grammar Learning from a Minimal Set of Seed Inputs
Sochor, H., Ferrarotti, F., & Kaufmann, D. (2024). Fuzzing-based grammar learning from a minimal set of seed inputs. Journal of Computer Languages, 78, 101252.
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Identification of similarities and clusters of bread baking recipes based on data of ingredients
Anlauf, S., Dorl, S., Hirz, T., Lasslberger, M., Grassmann, R., Himmelbauer, J., & Winkler, S. (2024). Identification of similarities and clusters of bread baking recipes based on data of ingredients. International Journal of Food Engineering, 0(0).
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In Scope? - The Definition of ‘AI System’ in the AI Act
Aufreiter, A., Aichinger, G., & Nessler, B.. (2025). In Scope? – The Definition of ’AI System’ in the AI Act. In Bernhard Nessler (p. and Vision (AIRoV)). innsbruck university press. https://doi.org/10.15203/99106-150-2-04
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Introducing a Linter in an Industrial Lua Code Base
Walchshofer, A., Fischer, S., Wöß, A., Duque-Torres, A., Löberbauer, M., & Koll, G. (2024, March). Introducing a Linter in an Industrial Lua Code Base. In 2024 IEEE International Conference on Software Analysis, Evolution and Reengineering-Companion (SANER-C) (pp. 191-198). IEEE.
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Learning the inhomogeneous term of a linear ODE
Sobieczky, F., Dudkin, E., & Zesinek, J. (2024). Learning the inhomogenous term of a linear ODE. Procedia Computer Science, 232, 1548–1553.
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MetaExploreX: A Visualisation Tool for Selecting and Constraining Metamorphic Relations
Duque-Torres, A., Pfahl, D., Klammer, C., & Fischer, S. (2024). MetaExploreX: A Visualisation Tool for Selecting and Constraining Metamorphic Relations. 2024 IEEE International Conference on Software Analysis, Evolution and Reengineering - Companion (SANER-C), 219–222.
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On Leaky-Integrate-and Fire as Spike-Train-Quantization Operator on Dirac-Superimposed Continuous-Time Signals
Moser, B. A., & Lunglmayr, M.. (2025). On Leaky Integrate-and-Fire as Spike-Train Quantization Operator on Dirac-Superimposed Continuous-Time Signals. In Bernhard Nessler (p. and Vision (AIRoV)). innsbruck university press. https://doi.org/10.15203/99106-150-2-69
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PAS - A Feature Selection Process Definition for Industrial Settings
Luftensteiner, S., Chasparis, G. C., & Küng, J. (2024). PAS - A Feature Selection Process Definition for Industrial Settings. Procedia Computer Science, 232, 308–316.
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Robustness of One-Class Visual Anomaly Detection Methods
Kromp, F., Brunner, D., Zellinger, J., Valentinitsch, A., Cakiroglu, O., Schachner, C., & Fischer, L.. (2025). Robustness of One-Class Visual Anomaly Detection Methods. In Bernhard Nessler (p. and Vision (AIRoV)). innsbruck university press. https://doi.org/10.15203/99106-150-2-35
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Semantic Modeling of Architecture Decision Records to Enable AI-based Analysis
Karetnikov, A., Ehrlinger, L., Buchgeher, G., & Geist, V. (2024). Semantic Modeling of Architecture Decision Records to Enable AI-based Analysis. 2024 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
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Spike-based QRS complex detection in ECG signals
Lunglmay, M., Windhager, D., Böck, C., Moser, B., Baronig, M., & Legenstein, R.. (2025). Spike-based QRS complex detection in ECG signals. In Bernhard Nessler (p. and Vision (AIRoV)). innsbruck university press. https://doi.org/10.15203/99106-150-2-71
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Subspace Corrected Relevance Learning with Application in Neuroimaging
van Veen, R., Tamboli, N. R. B., Lövdal, S., Meles, S. K., Renken, R. J., de Vries, G.-J., Arnaldi, D., Morbelli, S., Clavero, P., Obeso, J. A., Oroz, M. C. R., Leenders, K. L., Villmann, T., & Biehl, M. (2024). Subspace corrected relevance learning with application in neuroimaging. Artificial Intelligence in Medicine, 149, 102786.
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The Need for Speed: Efficient Exact Simulation of Silicon Dangling Bond Logic
Drewniok, J., Walter, M., & Wille, R. (2024). The Need for Speed: Efficient Exact Simulation of Silicon Dangling Bond Logic. 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC).
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Analysis and Propagation of Feature Revisions in Preprocessor-based Software Product Lines
Michelon, G. K., Assunção, W., Grünbacher, P., & Egyed, A.. (2024). Analysis and Propagation of Feature Revisions in Preprocessor-based Software Product Lines. None, None. https://doi.org/10.18420/SW2024_23
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Experiment Data: Human-in-the-loop Decision Support in Process Control Rooms
Amazu, C. W., Mietkiewicz, J., Abbas, A. N., Briwa, H., Perez, A. A., Baldissone, G., Demichela, M., Fissore, D., Madsen, A. L., & Leva, M. C. (2024). Experiment Data: Human-in-the-loop Decision Support in Process Control Rooms. Data in Brief, 110170.
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Investigating the Readability of Test Code: Combining Scientific and Practical Views
Winkler, D., Urbanke, P., & Ramler, R. (2024). Investigating the readability of test code. Empirical Software Engineering, 29(2).
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On Mitigating the Utility-Loss in Differentially Private Learning: A new Perspective by a Geometrically Inspired Kernel Approach
Kumar, M., Moser, B. A., & Fischer, L. (2024). On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach. Journal of Artificial Intelligence Research, 79, 515–567.
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Data Pipeline Quality: Influencing Factors, Root Causes of Data-related Issues, and Processing Problem Areas for Developers
Foidl, H., Golendukhina, V., Ramler, R., & Felderer, M. (2024). Data pipeline quality: Influencing factors, root causes of data-related issues, and processing problem areas for developers. Journal of Systems and Software, 207, 111855.
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Enhancing Control Room Operator Decision Making
Mietkiewicz, J.; Abbas, A.N.; Amazu, C.W.; Baldissone, G.; Madsen, A.L.; Demichela, M.; Leva, M.C. Enhancing Control Room Operator Decision Making. Processes 2024, 12, 328. https://doi.org/10.3390/pr12020328
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Hierarchical framework for interpretable and specialized deep reinforcement learning-based predictive maintenance
Abbas, A. N., Chasparis, G. C., & Kelleher, J. D. (2024). Hierarchical framework for interpretable and specialized deep reinforcement learning-based predictive maintenance. Data & Knowledge Engineering, 149, 102240.
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Innovating Industry with Research: eknows and Sysparency
Geist, V., Moser, M., Pichler, J., & Schnitzhofer, F. (2024). Innovating Industry with Research: eknows and Sysparency. IEEE Software, 1–7.
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Using Boolean Satisfiability for Exact Shuttling in Trapped-Ion Quantum Computers
Schoenberger, D., Hillmich, S., Brandl, M., & Wille, R. (2024). Using Boolean Satisfiability for Exact Shuttling in Trapped-Ion Quantum Computers. 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC).
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An Introduction to AI: System I & II
Nessler/Aufreiter/Mederitsch/Aichinger/Schmid, An Introduction to AI : System I & II, WU Tax Technology Conference 2024
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CantorNet - A Sandbox for Testing Geometrical and Topological Measures
Michal Lewandowski, Hamid Eghbalzadeh, & Bernhard A. Moser (2024). CantorNet: A Sandbox for Testing Topological and Geometrical Measures. In NeurIPS 2024 Workshop on Symmetry and Geometry in Neural Representations.
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Data Validation Utilizing Expert Knowledge and Shape Constraints
Bachinger, F., Ehrlinger, L., Kronberger, G., & Wöß, W. (2024). Data Validation Utilizing Expert Knowledge and Shape Constraints. Journal of Data and Information Quality.
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Enhancing Control Room Operator Decision Making
Mietkiewicz, J., Abbas, A. N., Amazu, C. W., Baldissone, G., Madsen, A. L., Demichela, M., & Leva, M. C.. (2024). Enhancing Control Room Operator Decision Making. In Processes (p. 328). MDPI AG. https://doi.org/10.3390/pr12020328
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2023
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Closing the Loop: Towards a Complete Metamorphic Testing Pipeline
Duque-Torres, A., & Pfahl, D. (2023). Closing the Loop: Towards a Complete Metamorphic Testing Pipeline. Lecture Notes in Computer Science, 146–151.
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Is It the Best Solution? Testing an Optimisation Algorithm with Metamorphic Testing
Duque-Torres, A., Klammer, C., Fischer, S., & Pfahl, D. (2023). Is It the Best Solution? Testing an Optimisation Algorithm with Metamorphic Testing. Lecture Notes in Computer Science, 339–354.
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Using AI-Based Code Completion for Domain-Specific Languages
Piereder, C., Fleck, G., Geist, V., Moser, M., & Pichler, J. (2023). Using AI-Based Code Completion for Domain-Specific Languages. Lecture Notes in Computer Science, 227–242.
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Comparative Analysis of SRAM PUF Temperature Susceptibility on Embedded Systems
Zeinzinger, M., Langer, J., Eibensteiner, F., Petz, P., Drack, L., Dorfmeister, D., & Ramler, R. (2023). Comparative Analysis of SRAM PUF Temperature Susceptibility on Embedded Systems. 2023 International Conference on Electrical, Computer and Energy Technologies (ICECET).
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DValidator: An approach for validating dependencies in build configurations
Macho, C., Oraze, F., & Pinzger, M. (2023). DValidator: An approach for validating dependencies in build configurations. Journal of Systems and Software, 111916.
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Rethinking data augmentation for adversarial robustness
Eghbal-zadeh, H., Zellinger, W., Pintor, M., Grosse, K., Koutini, K., Moser, B. A., Biggio, B., & Widmer, G. (2024). Rethinking data augmentation for adversarial robustness. Information Sciences, 654, 119838.
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A novel EGs-based framework for systematic propositional-formula simplification
Francès de Mas, J., & Bowles, J. (2023). A Novel EGs-Based Framework for Systematic Propositional-Formula Simplification. Logic-Based Program Synthesis and Transformation, 169–187.
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Deep Learning for tabular data
Kostromin, Oleg. (2023). Deep Learning for Tabular Data. Master Thesis, Johannes Kepler University Linz. https://epub.jku.at/obvulihs/content/titleinfo/9293186
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DEPS: Leveraging Hardware Faults for Binding Software to Hardware
Noll, T., & Fesefeldt, I. J.. (2023). 22. Kolloquium Programmiersprachen und Grundlagen der Programmierung. 22. Kolloquium Programmiersprachen Und Grundlagen Der Programmierung, 1 Online–Ressource (2023).. https://doi.org/10.18154/RWTH-2023-10034
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Functional trustworthiness of AI systems by statistically valid testing
Nessler, B., Hochreiter, S., & Doms, T. (2023). Functional trustworthiness of AI systems by statistically valid testing. Position paper to the current regulation and standardization effort of AI in Europe. SCCH Technical Report. https://doi.org/10.48550/arXiv.2310.02727
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Getting QuantumReady: A Framework for Exploiting Quantum Computing in SMEs
Hillmich, S., Bruckner, S., Ferrarotti, F., & Ramler, R. (2023). Getting QuantumReady: A Framework for Exploiting Quantum Computing in SMEs. Munich Quantum Software Forum (MQSF 2023)
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Secure Federated Learning with Kernel Affine Hull Machines
Kumar, M., Moser, B., & Fischer, L. (2023). Secure Federated Learning with Kernel Affine Hull Machines. ESANN 2023 Proceesdings.
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Specification-based Test Case Generation for C++ Engineering Software
Hamberger, P., Klammer, C., Luger, T., Moser, M., Pfeiffer, M., & Piereder, C. (2023). Specification-based Test Case Generation for C++ Engineering Software. 2023 IEEE International Conference on Software Maintenance and Evolution (ICSME).
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Towards a Complete Metamorphic Testing Pipeline
Duque-Torres, A., & Pfahl, D. (2023). Towards a Complete Metamorphic Testing Pipeline. 2023 IEEE International Conference on Software Maintenance and Evolution (ICSME).
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Towards an Ontology for Technical Security Standards
Illescas, J., Ehrlinger, L., Denk, G., & Buchgeher, G. (2023). Towards an Ontology for Technical Security Standards. 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA).
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Activity of Single Insect Olfactory Receptors Triggered by Airborne Compounds Recorded in Self-Assembled Tethered Lipid Bilayer Nanoarchitectures
Kleinheinz, D., D’Onofrio, C., Carraher, C., Bozdogan, A., Ramach, U., Schuster, B., Geiß, M., Valtiner, M., Knoll, W., & Andersson, J. (2023). Activity of Single Insect Olfactory Receptors Triggered by Airborne Compounds Recorded in Self-Assembled Tethered Lipid Bilayer Nanoarchitectures. ACS Applied Materials & Interfaces, 15(40), 46655–46667.
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An Information Theoretic Approach to Privacy-Preserving Interpretable and Transferable Learning
Kumar, M., Moser, B. A., Fischer, L., & Freudenthaler, B. (2023). An Information Theoretic Approach to Privacy-Preserving Interpretable and Transferable Learning. Algorithms, 16(9), 450.
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Automation and Development Effort in Continuous AI Development: A Practitioners’ Survey
Steidl, M., Golendukhina, V., Felderer, M., & Ramler, R. (2023). Automation and Development Effort in Continuous AI Development: A Practitioners’ Survey. 2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA).
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Compiler Optimization for Quantum Computing Using Reinforcement Learning
Quetschlich, N., Burgholzer, L., & Wille, R. (2023). Compiler Optimization for Quantum Computing Using Reinforcement Learning. 2023 60th ACM/IEEE Design Automation Conference (DAC).
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Design Automation for Cryogenic CMOS Circuits
van Santen, V. M., Walter, M., Klemme, F., Parihar, S. S., Pahwa, G., Chauhan, Y. S., Wille, R., & Amrouch, H. (2023). Design Automation for Cryogenic CMOS Circuits. 2023 60th ACM/IEEE Design Automation Conference (DAC).
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Documenting and Comparing OPC UA Information Models
S. Schöberl, B. Dorninger, A. Kern and V. Geist, "Documenting and Comparing OPC UA Information Models," 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA), Sinaia, Romania, 2023, pp. 1-8, doi: 10.1109/ETFA54631.2023.10275554.
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Dynamic Influence Diagram-Based Deep Reinforcement Learning Framework and Application for Decision Support for Operators in Control Rooms
Mietkiewicz, J., Abbas, A. N., Amazu, C. W., Madsen, A. L., & Baldissone, G. (2023). Dynamic Influence Diagram-Based Deep Reinforcement Learning Framework and Application for Decision Support for Operators in Control Rooms. Proceeding of the 33rd European Safety and Reliability Conference.
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Efficient Implementation of Quantum Circuit Simulation with Decision Diagrams
Hillmich, S., & Wille, R. (2024). Efficient Implementation of Quantum Circuit Simulation with Decision Diagrams. Synthesis Lectures on Engineering, Science, and Technology.
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Examining the Adoption of Knowledge Graphs in the Manufacturing Industry: A Comprehensive Review
Martinez-Gil, J., Hoch, T., Pichler, M., Heinzl, B., Moser, B., Kurniawan, K., Kiesling, E., & Krause, F. (2023). Examining the Adoption of Knowledge Graphs in the Manufacturing Industry: A Comprehensive Review. Artificial Intelligence in Manufacturing, 55–70.
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Exploring a Test Data-Driven Method for Selecting and Constraining Metamorphic Relations
Duque-Torres, A., Pfahl, D., Klammer, C., & Fischer, S. (2023). Exploring a Test Data-Driven Method for Selecting and Constraining Metamorphic Relations. 2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA).
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Iterative Design and Evaluation of a Low-Code Development Platform for Welding Robot Control
Schenkenfelder, B., Moser, M., Pfeiffer, M., Pichler, J., Salomon, C., & Winterer, M. (2023). Iterative Design and Evaluation of a Low-Code Development Platform for Welding Robot Control. 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA).
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Late Breaking Results From Hybrid Design Automation for Field-coupled Nanotechnologies
Hofmann, S., Walter, M., Servadei, L., & Wille, R. (2023). Late Breaking Results From Hybrid Design Automation for Field-coupled Nanotechnologies. 2023 60th ACM/IEEE Design Automation Conference (DAC).
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Leveraging Semantic Representations via Knowledge Graph Embeddings
Krause, F., Kurniawan, K., Kiesling, E., Martinez-Gil, J., Hoch, T., Pichler, M., Heinzl, B., & Moser, B. (2023). Leveraging Semantic Representations via Knowledge Graph Embeddings. Artificial Intelligence in Manufacturing, 71–85.
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Mixed-Dimensional Quantum Circuit Simulation with Decision Diagrams
Mato, K., Hillmich, S., & Wille, R. (2023). Mixed-Dimensional Quantum Circuit Simulation with Decision Diagrams. 2023 IEEE International Conference on Quantum Computing and Engineering (QCE).
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Multi-Stakeholder Perspective on Human-AI Collaboration in Industry 5.0
Hoch, T., Martinez-Gil, J., Pichler, M., Silvina, A., Heinzl, B., Moser, B., Eleftheriou, D., Estrada-Lugo, H. D., & Leva, M. C. (2023). Multi-Stakeholder Perspective on Human-AI Collaboration in Industry 5.0. Artificial Intelligence in Manufacturing, 407–421.
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Representing piecewise linear functions by functions with small arity
Koutschan, C., Moser, B., Ponomarchuk, A., & Schicho, J. (2023). Representing piecewise linear functions by functions with small arity. Applicable Algebra in Engineering, Communication and Computing.
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The Potential of Low-Code Development in the Manufacturing Industry
Schenkenfelder, B., Salomon, C., Buchgeher, G., Schossleitner, R., & Kerl, C. (2023). The Potential of Low-Code Development in the Manufacturing Industry. 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA).
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Towards Automatic Generation of Amplified Regression Test Oracles
Duque-Torres, A., Klammer, C., Pfahl, D., Fischer, S., & Ramler, R. (2023). Towards Automatic Generation of Amplified Regression Test Oracles. 2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA).
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Versatile Signal Distribution Networks for Scalable Placement and Routing of Field-coupled Nanocomputing Technologies
Walter, M., Hien, B., & Wille, R. (2023). Versatile Signal Distribution Networks for Scalable Placement and Routing of Field-coupled Nanocomputing Technologies. 2023 IEEE Computer Society Annual Symposium on VLSI (ISVLSI).
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An Approach for Safe and Secure Software Protection Supported by Symbolic Execution
Dorfmeister, D., Ferrarotti, F., Fischer, B., Haslinger, E., Ramler, R., & Zimmermann, M. (2023). An Approach for Safe and Secure Software Protection Supported by Symbolic Execution. Communications in Computer and Information Science, 67–78.
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Database and Expert Systems Applications - DEXA 2023 Workshops Proceedings
Kotsis, G., Tjoa, A. M., Khalil, I., Moser, B., Mashkoor, A., Sametinger, J., & Khan, M. (Eds.). (2023). Database and Expert Systems Applications - DEXA 2023 Workshops. Communications in Computer and Information Science.
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Deep fuzzy mapping nonparametric model for real-time demand estimation in water distribution systems: A new perspective
Zhang, Q., Yang, J., Zhang, W., Kumar, M., Liu, J., Liu, J., & Li, X. (2023). Deep fuzzy mapping nonparametric model for real-time demand estimation in water distribution systems: A new perspective. Water Research, 241, 120145.
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DSD: The Data Source Description Vocabulary
Ehrlinger, L., Schrott, J., & Wöß, W. (2023). DSD: The Data Source Description Vocabulary. Communications in Computer and Information Science, 3–10.
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Error mitigation enables PET radiomic cancer characterization on quantum computers
Moradi, S., Spielvogel, C., Krajnc, D., Brandner, C., Hillmich, S., Wille, R., Traub-Weidinger, T., Li, X., Hacker, M., Drexler, W., & Papp, L. (2023). Error mitigation enables PET radiomic cancer characterization on quantum computers. European Journal of Nuclear Medicine and Molecular Imaging.
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GOLDCASE: A Generic Ontology Layer for Data Catalog Semantics
Schrott, J., Weidinger, S., Tiefengrabner, M., Lettner, C., Wöß, W., & Ehrlinger, L. (2023). GOLDCASE: A Generic Ontology Layer for Data Catalog Semantics. Communications in Computer and Information Science, 26–38.
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Measuring Overhead Costs of Federated Learning Systems by Eavesdropping
Meindl, R., & Moser, B. A. (2023). Measuring Overhead Costs of Federated Learning Systems by Eavesdropping. Communications in Computer and Information Science, 33–42.
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Membership-Mappings for Practical Secure Distributed Deep Learning
Kumar, M., Zhang, W., Fischer, L., & Freudenthaler, B. (2023). Membership-Mappings for Practical Secure Distributed Deep Learning. IEEE Transactions on Fuzzy Systems, 1–14.
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Model-based Testing for a Family of Mobile Applications: Industrial Experiences
Fischer, S., Ramler, R., Assunção, W. K. G., Egyed, A., Gradl, C., & Auberger, S. (2023). Model-based Testing for a Family of Mobile Applications. Proceedings of the 27th ACM International Systems and Software Product Line Conference - Volume A.
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Representation Theorems Obtained by Mining across Web Sources for Hints
Caminati, M. B., & Bowles, J. K. F.. (2023). Representation Theorems Obtained by Mining across Web Sources for Hints. In 2023 6th International Conference on Information and Computer Technologies (ICICT) (pp. 203–210). IEEE. https://doi.org/10.1109/icict58900.2023.00041
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Automated Cross Channel Temperature Predictions for the PFR Lime Kiln Operating Support
Kychkin, A. V., Chasparis, G. C., & Ellero, S. (2023). Automated Cross Channel Temperature Predictions for the PFR Lime Kiln Operating Support. 2023 31st Mediterranean Conference on Control and Automation (MED).
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Automating Data Quality Monitoring with Reference Data Profiles
Ehrlinger, L., Werth, B., & Wöß, W. (2023). Automating Data Quality Monitoring with Reference Data Profiles. Data Management Technologies and Applications, 24–44.
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Compression of Qubit Circuits: Mapping to Mixed-Dimensional Quantum Systems
Mato, K., Hillmich, S., & Wille, R. (2023). Compression of Qubit Circuits: Mapping to Mixed-Dimensional Quantum Systems. 2023 IEEE International Conference on Quantum Software (QSW).
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Examples of Long-Term Science-Industry Partnerships for Translational Computer Science
Travnicek, C., Nowak, V., Ramler, R., Fischer, L., & Bühler, K. (2023). Examples of Long-Term Science–Industry Partnerships for Translational Computer Science. Computing in Science & Engineering, 25(1), 52–56.
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Four Factors Affecting Missing Data Imputation
Hackl, A., Zeindl, J., & Ehrlinger, L. (2023). Four Factors Affecting Missing Data Imputation. 35th International Conference on Scientific and Statistical Database Management.
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Modeling the Extra Pass in Basketball
Supola, B., Hoch, T., & Baca, A. (2023). Modeling the Extra Pass in Basketball. Advances in Intelligent Systems and Computing, 178–181.
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Predicting Good Quantum Circuit Compilation Options
Quetschlich, N., Burgholzer, L., & Wille, R. (2023). Predicting Good Quantum Circuit Compilation Options. 2023 IEEE International Conference on Quantum Software (QSW).
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Recommending Solution Paths for Solving Optimization Problems with Quantum Computing
Poggel, B., Quetschlich, N., Burgholzer, L., Wille, R., & Lorenz, J. M. (2023). Recommending Solution Paths for Solving Optimization Problems with Quantum Computing. 2023 IEEE International Conference on Quantum Software (QSW).
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Scalable Physical Design for Silicon Dangling Bond Logic: How a 45° Turn Prevents the Reinvention of the Wheel
Hofmann, S., Walter, M., & Wille, R. (2023). Scalable Physical Design for Silicon Dangling Bond Logic: How a 45° Turn Prevents the Reinvention of the Wheel. 2023 IEEE 23rd International Conference on Nanotechnology (NANO).
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Towards Vertical Privacy-Preserving Symbolic Regression via Secure Multiparty Computation
Nguyen Duy, D., Affenzeller, M., & Nikzad-Langerodi, R. (2023). Towards Vertical Privacy-Preserving Symbolic Regression via Secure Multiparty Computation. Proceedings of the Companion Conference on Genetic and Evolutionary Computation.
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Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning
Cinà, A. E., Grosse, K., Demontis, A., Vascon, S., Zellinger, W., Moser, B. A., Oprea, A., Biggio, B., Pelillo, M., & Roli, F. (2023). Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. ACM Computing Surveys, 55(13s), 1–39.
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Dynamic spillovers across precious metals and oil realized volatilities: Evidence from quantile extended joint connectedness measures
Cunado, J., Chatziantoniou, I., Gabauer, D., de Gracia, F. P., & Hardik, M. (2023). Dynamic spillovers across precious metals and oil realized volatilities: Evidence from quantile extended joint connectedness measures. Journal of Commodity Markets, 30, 100327.
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HE-MAN - Homomorphically Encrypted MAchine learning with oNnx models
Nocker, M., Drexel, D., Rader, M., Montuoro, A., & Schöttle, P. (2023). HE-MAN – Homomorphically Encrypted MAchine learning with oNnx models. Proceedings of the 2023 8th International Conference on Machine Learning Technologies.
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Integration and risk transmission in the market for crude oil
Chatziantoniou, I., Gabauer, D., & Gupta, R. (2023). Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach. Resources Policy, 84, 103729.
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Neural network architecture optimization using automated machine learning for borehole resistivity measurements
Shahriari, M., Pardo, D., Kargaran, S., & Teijeiro, T. (2023). Neural network architecture optimization using automated machine learning for borehole resistivity measurements. Geophysical Journal International, 234(3), 2488–2501.
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Optimized Density Matrix Representations: Improving the Basis for Noise-Aware Quantum Circuit Design Tools
Grurl, T., Fuß, J., & Wille, R. (2023). Optimized Density Matrix Representations : Improving the Basis for Noise-Aware Quantum Circuit Design Tools. 2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL).
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Towards an Automated Framework for Realizing Quantum Computing Solutions
Quetschlich, N., Burgholzer, L., & Wille, R. (2023). Towards an Automated Framework for Realizing Quantum Computing Solutions. 2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL).
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Using Architecture Decision Records in Open Source Projects - An MSR Study on GitHub
Buchgeher, G., Schöberl, S., Geist, V., Dorninger, B., Haindl, P., & Weinreich, R. (2023). Using Architecture Decision Records in Open Source Projects – An MSR Study on GitHub. IEEE Access, 1–1.
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A New AKE Protocol for the Application in QKDNs Without Trusted Nodes
Bruckner, S. (2023). A New AKE Protocol for the Application in QKDNs Without Trusted Nodes. Master Thesis, University of Applied Sciences Upper Austria, Hagenberg, May 2023
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A Survey on Legal Question Answering Systems
Martinez-Gil, J. (2023). A survey on legal question–answering systems. Computer Science Review, 48, 100552.
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An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization
Kromp, F., Wagner, R., Balaban, B., Cottin, V., Cuevas-Saiz, I., Schachner, C., Fancsovits, P., Fawzy, M., Fischer, L., Findikli, N., Kovačič, B., Ljiljak, D., Martínez-Rodero, I., Parmegiani, L., Shebl, O., Min, X., & Ebner, T. (2023). An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization. Scientific Data, 10(1).
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Analysis of Library Dependency Networks of Package Managers Used in iOS Development
Rahkema, K., Pfahl, D., & Ramler, R. (2023). Analysis of Library Dependency Networks of Package Managers Used in iOS Development. 2023 IEEE/ACM 10th International Conference on Mobile Software Engineering and Systems (MOBILESoft).
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Applying a Genetic Algorithm for Test Suite Reduction in Industry
Stadler, P., Plösch, R., & Ramler, R. (2023). Applying a Genetic Algorithm for Test Suite Reduction in Industry. Lecture Notes in Business Information Processing, 63–83.
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Behavioural Theory of Reflective Algorithms
Ferrarotti, F., & Schewe, K.-D. (2023). Behavioural Theory of Reflective Algorithms. Lecture Notes in Computer Science, 238–244.
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Bug or not Bug? Analysing the Reasons Behind Metamorphic Relation Violations
Duque-Torres, A., Pfahl, D., Klammer, C., & Fischer, S. (2023). Bug or not Bug? Analysing the Reasons Behind Metamorphic Relation Violations. 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
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Data set for "Investigating the Readability of Test Code: Combining Scientific and Practical Views"
Winkler, D., Urbanke, P., & Ramler, R.. (2023). Data set for "Investigating the Readability of Test Code: Combining Scientific and Practical Views" [Data set]. In None (p. None). TU Wien. https://doi.org/10.48436/NC184-WCQ35
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Decision Making for Process Control Management in Control Rooms: A Survey Methodology and Initial Findings
Amazu C., Abbas A., Demichela M., Fissore D., (2023). Decision Making for Process Control Management in Control Rooms: a Survey Methodology and Initial Findings, Chemical Engineering Transactions, 99, 271-276.
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Design of a Rowhammer-Based Unique Hardware Identification Mechanism
Fischer, B. (2023). Design of a Rowhammer-Based Unique Hardware Identification Mechanism. Master Thesis, University of Applied Sciences Upper Austria, Hagenberg. May 2023.
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Efficient Implementation of LIMDDs for Quantum Circuit Simulation
Vinkhuijzen, L., Grurl, T., Hillmich, S., Brand, S., Wille, R., Laarman, A. (2023). Efficient Implementation of LIMDDs for Quantum Circuit Simulation. Model Checking Software. SPIN 2023. LNCS 13872. Springer,
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Exploration of Reflective ASMs for Security
Tong, L., Xu, K., Hu, J., Ferrarotti, F., & Schewe, K.-D. (2023). Exploration of Reflective ASMs for Security. Lecture Notes in Computer Science, 185–192.
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Insights from Building a GUI Testing Tool
Fischer, S. (2023). Insights from Building a GUI Testing Tool. 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
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Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way
Affenzeller, M., Bögl, M., Fischer, L., Sobieczky, F., Yang, K., & Zenisek, J. (2022). Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way. 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC).
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R2C: AOCR-Resilient Diversity with Reactive and Reflective Camouflage
Berlakovich, F., & Brunthaler, S. (2023). R2C: AOCR-Resilient Diversity with Reactive and Reflective Camouflage. Proceedings of the Eighteenth European Conference on Computer Systems.
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Testing of Highly Configurable Cyber-Physical Systems - Results from a Two-Phase Multiple Case Study
Fischer, S., Klammer, C., Fernández, A. M. G., Rabiser, R., & Ramler, R. (2023). Testing of highly configurable cyber–physical systems — Results from a two-phase multiple case study. Journal of Systems and Software, 199, 111624.
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The need for a non-invasive technology for endometriosis detection and care
Hine, A., Bowles, J., & Webber, T.. (2023). The Need for a Non-Invasive Technology for Endometriosis Detection and Care. In Studies in Health Technology and Informatics (p. None). IOS Press. https://doi.org/10.3233/shti230073
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The Pipeline for the Continuous Development of Artificial Intelligence Models - Current State of Research and Practice
Steidl, M., Felderer, M., & Ramler, R. (2023). The pipeline for the continuous development of artificial intelligence models—Current state of research and practice. Journal of Systems and Software, 199, 111615.
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Automatic Implementation and Evaluation of Error-Correcting Codes for Quantum Computing: An Open-Source Framework for Quantum Error Correction
Grurl, T., Pichler, C., Fuß, J., & Wille, R. (2023). Automatic Implementation and Evaluation of Error-Correcting Codes for Quantum Computing: An Open-Source Framework for Quantum Error Correction. 2023 36th International Conference on VLSI Design and 2023 22nd International Conference on Embedded Systems (VLSID).
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Climate Risks and Forecasting Stock Market Returns in Advanced Economies over a Century
Balcilar, M., Gabauer, D., Gupta, R., & Pierdzioch, C. (2023). Climate Risks and Forecasting Stock Market Returns in Advanced Economies over a Century. Mathematics, 11(9), 2077.
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Contemporaneous and lagged R2 decomposed connectedness approach: New evidence from the energy futures market
Balli, F., Ozer-Balli, H., Dang, T., & Gabauer, D. (2023). Return Transmission Mechanism Across Energy Futures: New Evidence from <i>R</i> <sup>2</sup> Decomposed Connectedness Measures. SSRN Electronic Journal.
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Continuous Development of AI: a Practitioners' Survey
Steidl, M., Golendukhina, V., Felderer, M., & Ramler, R.. (2023). Continuous Development of AI: a Practitioners' Survey [Data set]. In None (p. None). Zenodo. https://doi.org/10.5281/ZENODO.7838939
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Introducing QRogue: Teaching Quantum Computing Using a Rogue-like Game Concept
Artner, M., Wallner, G., & Wille, R. (2023). Introducing QRogue: Teaching Quantum Computing Using a Rogue-like Game Concept. Proceedings of the 18th International Conference on the Foundations of Digital Games.
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Oil price shocks and exchange rate dynamics: Evidence from decomposed and partial connectedness measures for oil importing and exporting economies
Chatziantoniou, I., Elsayed, A. H., Gabauer, D., & Gozgor, G. (2023). Oil price shocks and exchange rate dynamics: Evidence from decomposed and partial connectedness measures for oil importing and exporting economies. Energy Economics, 120, 106627.
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Ontology-based Multi-Perspective Process Mining in Laboratories: A Case Study
Mayrhuber, E., Helm, E., & Ehrlinger, L. (2024). Ontology-Based Multi-perspective Process Mining in Laboratories: A Case Study. Process Mining Workshops, 283–295.
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Opening the black-box of Neighbor Embeddings with Hotelling’s T2 statistic and Q-residuals
Rainer, R. J., Mayr, M., Himmelbauer, J., & Nikzad-Langerodi, R. (2023). Opening the black-box of Neighbor Embeddings with Hotelling’s T2 statistic and Q-residuals. In Chemometrics and Intelligent Laboratory Systems (Vol. 238, p. 104840). Elsevier BV.
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Transfer Learning for Semantic Similarity Measures based on Symbolic Regression
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2023). Transfer learning for semantic similarity measures based on symbolic regression. Journal of Intelligent & Fuzzy Systems, 45(1), 37–49.
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What is Driving Connectedness? Stylized Facts from Mean and Volatility Dynamics
Antonakakis, N., Gabauer, D., & Chatziantoniou, I. (2023). What is Driving Connectedness? Stylized Facts from Mean and Volatility Dynamics. SSRN Electronic Journal.
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Analysis and Propagation of Feature Revisions in Preprocessor-based Software Product Lines
Michelon, G. K., Assunção, W. K. G., Grünbacher, P., & Egyed, A.. (2023). Analysis and Propagation of Feature Revisions in Preprocessor-based Software Product Lines. In 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) (pp. 284–295). IEEE. https://doi.org/10.1109/saner56733.2023.00035
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Detection of Sensor-To-Sensor Variations using Explainable AI
Seifi, S., Schober, S. A., Carbonelli, C., Servadei, L., & Wille, R. (2023). Detection of Sensor-to-Sensor Variations Using Explainable AI. 2023 Smart Systems Integration Conference and Exhibition (SSI).
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Editorial: Automated data curation and data governance automation
Talburt, J. R., Ehrlinger, L., & Magruder, J. (2023). Editorial: Automated data curation and data governance automation. Frontiers in Big Data, 6.
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Global challenges reflected in software process improvement
Colomo‐Palacios, R., Messnarz, R., & Biró, M. (2023). Global challenges reflected in software process improvement. Journal of Software: Evolution and Process, 35(9). Portico.
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Leveraging and Evaluating Automatic Code Summarization for JPA Program Comprehension
Mayer, R., Moser, M., & Geist, V. (2023). Leveraging and Evaluating Automatic Code Summarization for JPA Program Comprehension. 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
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Model-free connectedness measures
Gabauer, D., Chatziantoniou, I., & Stenfors, A. (2023). Model-free connectedness measures. Finance Research Letters, 54, 103804.
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Modeling the extra pass in basketball – an assesment of one of the most crucial skills for creating great ball movement
Supola, B., Hoch, T., & Baca, A. (2023). Modeling the extra pass in basketball – an assessment of one of the most crucial skills for creating great ball movement. International Journal of Computer Science in Sport, 22(1), 13–29.
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MQT QMAP: Efficient Quantum Circuit Mapping
Wille, R., & Burgholzer, L. (2023). MQT QMAP. Proceedings of the 2023 International Symposium on Physical Design.
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Partial least squares regression with multiple domains
Mikulasek, B., Fonseca Diaz, V., Gabauer, D., Herwig, C., & Nikzad‐Langerodi, R. (2023). Partial least squares regression with multiple domains. Journal of Chemometrics. Portico.
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A human blastocyst dataset including clinical annotations to benchmark deep learning architectures for in vitro fertilization
Kromp, F., Wagner, R., Balaban, B., Cottin, V., Saiz, I. C., Dacho, C., Fancsovits, P., Fawzy, M., Fischer, L., Findikli, N., Kovacic, B., Ljiljak, D., Rodero, I. M., Parmegiani, L., Shebl, O., Min, X., & Ebner, T.. (2023). A human blastocyst dataset including clinical annotations to benchmark deep learning architectures for in vitro fertilization. In None (p. None). figshare. https://doi.org/10.6084/M9.FIGSHARE.20123153
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Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation
Dinu M., Holzleitner M., Beck M., Nguyen H., Huber A., Eghbal-zadeh H., Moser B., Pereverzyev S., Hochreiter S., Zellinger W. Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. ICLR 2023
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Automatic Bounding Box Annotation with Small Training Data Sets for Industrial Manufacturing
Geiß, M., Wagner, R., Baresch, M., Steiner, J., & Zwick, M. (2023). Automatic Bounding Box Annotation with Small Training Datasets for Industrial Manufacturing. Micromachines, 14(2), 442.
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KI-Net: AI-based Optimization in Industrial Manufacturing - A Project Overview
Freudenthaler, B., Martinez-Gil, J., Fensel, A., Höfig, K., Huber, S., & Jacob, D. (2022). KI-Net: AI-Based Optimization in Industrial Manufacturing—A Project Overview. Lecture Notes in Computer Science, 554–561.
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Measuring the G20 Stock Market Return Transmission Mechanism: Evidence From the R2 Connectedness Approach
Naeem, M. A., Chatziantoniou, I., Gabauer, D., & Karim, S. (2023). Measuring the G20 Stock Market Return Transmission Mechanism: Evidence From the R2 Connectedness Approach. SSRN Electronic Journal.
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Modeling the formation of defensive gaps in basketball: Cutting on a teammate’s drive
Supola, B., Hoch, T., & Baca, A. (2023). Modeling the formation of defensive gaps in basketball: Cutting on a teammate’s drive. PLOS ONE, 18(2), e0281467.
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Neurofuzzy Semantic Similarity Measurement
Martinez-Gil, J., Mokadem, R., Küng, J., & Hameurlain, A. (2023). Neurofuzzy semantic similarity measurement. Data & Knowledge Engineering, 145, 102155.
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Optimising Manufacturing Process with Bayesian Learning and Knowledge Graphs
Chhetri, T. R., Aghaei, S., Fensel, A., Göhner, U., Gül-Ficici, S., & Martinez-Gil, J. (2022). Optimising Manufacturing Process with Bayesian Structure Learning and Knowledge Graphs. Lecture Notes in Computer Science, 594–602.
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Österreich in den europäischen Datenräumen: Visionspapier
Ruth Aigner, Norbert Amlacher, Paolo Budroni, ..., Hannes Gütler (2023). Österreich in den europäischen Datenräumen: Visionspapier. Data Intelligence Offensive. https://dataintelligence.at/wp-content/uploads/2023/11/DIO_Visionspapier_Oesterreich-in-den-Datenraeumen_final_2023.pdf
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Predictive Modeling for Flexibility Load Forecasting in Prosumer Communities
Georgios C. Chasparis, "Predictive Modeling for Flexibility Load Forecasting in Prosumer Communities," IEWT'23, Vienna, Austria, 2023.
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Representing Technical Standards as Knowledge Graph to Guide the Design of Industrial Systems
Illescas, J., Buchgeher, G., Ehrlinger, L., Gabauer, D., & Martinez-Gil, J. (2022). Representing Technical Standards as Knowledge Graph to Guide the Design of Industrial Systems. Lecture Notes in Computer Science, 603–610.
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A SAT Encoding for Optimal Clifford Circuit Synthesis
Schneider, S., Burgholzer, L., & Wille, R. (2023). A SAT Encoding for Optimal Clifford Circuit Synthesis. Proceedings of the 28th Asia and South Pacific Design Automation Conference.
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Compilation of Entangling Gates for High-Dimensional Quantum Systems
Mato, K., Ringbauer, M., Hillmich, S., and Wille, R. (2023). Compilation of Entangling Gates for High-Dimensional Quantum Systems. In: Asia and South Pacific Design Automation Conference (ASPDAC). ACM.
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Decision Diagrams for Quantum Computing
Wille, R., Hillmich, S., & Burgholzer, L. (2023). Decision Diagrams for Quantum Computing. In: Rasit O. Topaloglu (Ed.), Design Automation of Quantum Computers. Springer, 2023.
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Designing a Test Model for a Configurable System: An Exploratory Study of Preprocessor Directives and Feature Toggles
Fischer, S., Michelon, G. K., Assunção, W. K. G., Ramler, R., & Egyed, A. (2023). Designing a Test Model for a Configurable System: An Exploratory Study of Preprocessor Directives and Feature Toggles. Proceedings of the 17th International Working Conference on Variability Modelling of Software-Intensive Systems.
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Differentially private transferrable deep learning with membership-mappings
Kumar, M. (2022). Differentially private transferrable deep learning with membership-mappings. Advances in Computational Intelligence, 3(1).
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Dynamic Connectedness among the Implied Volatilities of Oil Prices and Financial Assets: New Evidence of the COVID-19 Pandemic
Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., & de Gracia, F. P. (2023). Dynamic connectedness among the implied volatilities of oil prices and financial assets: New evidence of the COVID-19 pandemic. International Review of Economics & Finance, 83, 114–123.
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Equivalence Checking of Parameterized Quantum Circuits: Verifying the Compilation of Variational Quantum Algorithms
Peham, T., Burgholzer, L., & Wille, R. (2023). Equivalence Checking of Parameterized Quantum Circuits. Proceedings of the 28th Asia and South Pacific Design Automation Conference.
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Exploiting Reversible Computing for Verification: Potential, Possible Paths, and Consequences
Burgholzer, L., & Wille, R. (2023). Exploiting Reversible Computing for Verification. Proceedings of the 28th Asia and South Pacific Design Automation Conference.
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Gathering Expert Knowledge in Process Industry
Luftensteiner, S., Chasparis, G. C., & Mayr, M. (2023). Gathering Expert Knowledge in Process Industry. Procedia Computer Science, 217, 960–968.
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Improving Offline Deep Learning Models by Censored Online Data
Luftensteiner, S., & Zwick, M. (2023). Improving Virtual Sensor Models by Censored Online Data. Procedia Computer Science, 217, 938–947.
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IndustrialEdgeML - End-to-end edge-based computer vision system for Industry 5.0
Wagner, R., Matuschek, M., Knaack, P., Zwick, M., & Geiß, M. (2023). IndustrialEdgeML - End-to-end edge-based computer vision system for Industry 5.0. Procedia Computer Science, 217, 594–603.
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Machine-Learning Based Metadata Extraction for Smart Patient Records
Frame, C., Janjic, V., Shahriari, M., & Rossbory, M. (2022). Machine-Learning Based Metadata Extraction for Smart Patient Records. 4th International Workshop on Adaptive and Personalized Privacy and Security (APPS 2022).
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Model‐based process improvement recommendation approaches
Biró, M., Colomo‐Palacios, R., & Messnarz, R. (2022). Model‐based process improvement recommendation approaches. Journal of Software: Evolution and Process, 35(8). Portico.
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Optimizing Readability Using Genetic Algorithms
Martinez-Gil, J. (2024). Optimizing readability using genetic algorithms. Knowledge-Based Systems, 284, 111273.
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Software Tools for Decoding Quantum Low-Density Parity Check Codes
Berent, L., Burgholzer, L., & Wille, R. (2023). Software Tools for Decoding Quantum Low-Density Parity-Check Codes. Proceedings of the 28th Asia and South Pacific Design Automation Conference.
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Time-varying spillover of US trade war on the growth of emerging economies
Çepni, O., Gabauer, D., Gupta, R., & Ramabulana, K. (2023). Time-Varying Spillover of us Trade War on the Growth of Emerging Economies. The Journal of Developing Areas, 57(1), 167–181.
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Using technology to enhance community health and territorial resources access
Portela, D. S., Webber, T., & Bowles, J.. (2023). Using Technology to Enhance Community Health and Territorial Resources Access. In Studies in Health Technology and Informatics (p. None). IOS Press. https://doi.org/10.3233/shti230490
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2022
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A Comparative Study of Ensemble Techniques Based on Genetic Programming: A Case Study in Semantic Similarity Assessment
Martinez-Gil, J. (2022). A Comparative Study of Ensemble Techniques Based on Genetic Programming: A Case Study in Semantic Similarity Assessment. International Journal of Software Engineering and Knowledge Engineering, 33(02), 289–312.
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A Framework for Evaluating the Readability of Test Code in the Context of Code Maintainability: A Family of Empirical Studies
Urbanke, P. (2022). A framework for evaluating the readability of test code in the context of code maintainability: A family of empirical studies [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.103606
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Approximating Decision Diagrams for Quantum Circuit Simulation.
Hillmich, S., Zulehner, A., Kueng, R., Markov, I. L., & Wille, R. (2022). Approximating Decision Diagrams for Quantum Circuit Simulation. ACM Transactions on Quantum Computing, 3(4), 1–21.
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Compact High-Performance Vibration Sensor Based on Single-Backplate MEMS Technology
Goswami, S., Bretthauer, C., Bogner, A., Basavanna, A., Anzinger, S., Haubold, M., Lorenz, G., Strasser, J., Weber, D., Servadei, L., & Wille, R. (2022). Compact High-Performance Vibration Sensor Based on Single-Backplate MEMS Technology. 2022 IEEE Sensors.
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Multi-Cloud Query Optimisation with Accurate and Efficient Quoting
Wojtowicz, D. T., Yin, S., Martinez-Gil, J., Morvan, F., & Hameurlain, A. (2022). Multi-Cloud Query Optimisation with Accurate and Efficient Quoting. 2022 IEEE International Conference on Big Data (Big Data).
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Three-Input NPN Class Gate Library for Atomic Silicon Quantum Dots.
Vieira, M. D., Ng, S. S. H., Walter, M., Wille, R., Walus, K., Ferreira, R. S., Neto, O. P. V., & Nacif, J. A. M. (2022). Three-Input NPN Class Gate Library for Atomic Silicon Quantum Dots. IEEE Design & Test, 39(6), 147–155.
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Uncertainty-based Meta-Reinforcement Learning for Robust Radar Tracking.
Ott, J., Servadei, L., Mauro, G., Stadelmayer, T., Santra, A., & Wille, R. (2022). Uncertainty-based Meta-Reinforcement Learning for Robust Radar Tracking. International Conference on Machine Learning and Applications (ICMLA).
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Utilizing Explainable AI for improving the Performance of Neural Networks.
Sun, Huawei, Servadei, Lorenzo, Feng, Hao, Stephan, Michael, Wille, Robert, & Santra, Avik. (2022). Utilizing Explainable AI for improving the Performance of Neural Networks (Version 1). arXiv.
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Analysing the Relationship between Dependency Definition and Updating Practice when Using Third-Party Libraries
Rahkema, K., & Pfahl, D. (2022). Analysing the Relationship Between Dependency Definition and Updating Practice When Using Third-Party Libraries. Lecture Notes in Computer Science, 90–107.
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Fuzzing-Based Grammar Inference
Sochor, H., Ferrarotti, F., & Kaufmann, D. (2022). Fuzzing-Based Grammar Inference. Lecture Notes in Computer Science, 72–86.
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Independent policy, dependent outcomes: A game of cross-country dominoes across European yield curves
Stenfors, A., Chatziantoniou, I., & Gabauer, D. (2022). Independent policy, dependent outcomes: A game of cross-country dominoes across European yield curves. Journal of International Financial Markets, Institutions and Money, 81, 101658.
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Inferring Metamorphic Relations from JavaDocs: A Deep Dive Into the MeMo Approach
Duque-Torres, A., & Pfahl, D. (2022). Inferring Metamorphic Relations from JavaDocs: A Deep Dive into the MeMo Approach. Lecture Notes in Computer Science, 418–432.
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MMFT Droplet Simulator: Efficient Simulation of Droplet-based Mocrofluidic Devices
Fink, G., Costamoling, F., & Wille, R. (2022). MMFT Droplet Simulator: Efficient Simulation of Droplet-based Microfluidic Devices. Software Impacts, 14, 100440.
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Preliminary Findings on the Occurrence and Causes of Data Smells in a Real-World Business Travel Data Processing Pipeline
Golendukhina, V., Foidl, H., Felderer, M., & Ramler, R. (2022). Preliminary findings on the occurrence and causes of data smells in a real-world business travel data processing pipeline. Proceedings of the 2nd International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things.
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Requirements for Anomaly Detection Techniques for Microservices
Steidl, M., Gattringer, M., Felderer, M., Ramler, R., & Shahriari, M. (2022). Requirements for Anomaly Detection Techniques for Microservices. Lecture Notes in Computer Science, 37–52.
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A Refinement Based Algorithm for Learning Program Input Grammars
Sochor, H., & Ferrarotti, F. (2022). A Refinement Based Algorithm for Learning Program Input Grammars. Lecture Notes in Computer Science, 138–156.
Zur Publikation -
AI-based Code Completion for Domain Specific Languages
Piereder, C. (2022). AI-based Code Completion for Domain Specific Languages. Master Thesis, University of Applied Sciences, Hagenberg. October 2022.
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Assessing Industrial End-User Programming of Robotic Production Cells: A controlled experiment
Mayr-Dorn, C., Winterer, M., Salomon, C., Hohensinger, D., & Fürschuss, H. (2023). Assessing industrial end-user programming of robotic production cells: A controlled experiment. Journal of Systems and Software, 195, 111547.
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Forecasting stock-market tail risk and connectedness in advanced economies over a century: The role of gold-to-silver and gold-to-platinum
Salisu, A. A., Pierdzioch, C., Gupta, R., & Gabauer, D. (2022). Forecasting stock-market tail risk and connectedness in advanced economies over a century: The role of gold-to-silver and gold-to-platinum price ratios. International Review of Financial Analysis, 83, 102300.
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How Do Deep-Learning Framework Versions Affect the Reproducibility of Neural Network Models?
Shahriari, M., Ramler, R., & Fischer, L. (2022). How Do Deep-Learning Framework Versions Affect the Reproducibility of Neural Network Models? Machine Learning and Knowledge Extraction, 4(4), 888–911.
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Potential of a Deep Convolutional Neural Network in the Selection of Human Blastocysts to Predict Clinical Pregnancy and Live Birth
Ebner, T., Wagner, R., Fischer, L., Shebl, O., Dacho, C., & Kromp, F. (2022). POTENTIAL OF A DEEP CONVOLUTIONAL NEURAL NETWORK IN THE SELECTION OF HUMAN BLASTOCYSTS TO PREDICT CLINCIAL PREGNANCY AND LIVE BIRTH. Fertility and Sterility, 118(4), e132.
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A Digital Platform to Facilitate the Resilience of Rural Territories
Martinez-Gil, J., Pichler, M., Lentini, G., Mazzeschi, V., Doukhan, G., & Belet, C. (2022). A Digital Platform to Facilitate the Resilience of Rural Territories. Journal of Information & Knowledge Management, 21(03).
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A Toolchain for Testing OPC UA Interfaces
Walchshofer, A., Klammer, C., & Fischer, S. (2022). A toolchain for testing OPC UA interfaces. 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA).
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Adaptive Compilation Mulit-Level Quantum Operations
Mato, K., Ringbauer, M., Hillmich, S., & Wille, R. (2022). Adaptive Compilation of Multi-Level Quantum Operations. 2022 IEEE International Conference on Quantum Computing and Engineering (QCE).
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Comparing and Validating Neural Networks for Automatic Code Summarization
Mayer, R. (2022). Comparing and Validating Neural Networks for Automatic Code Summarization. Master Thesis, University of Applied Sciences, Hagenberg. September 2022.
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Crude oil and Islamic sectoral stocks: Asymmetric connectedness and investment strategies
Adekoya, O. B., Akinseye, A. B., Antonakakis, N., Chatziantoniou, I., Gabauer, D., & Oliyide, J. (2022). Crude oil and Islamic sectoral stocks: Asymmetric TVP-VAR connectedness and investment strategies. Resources Policy, 78, 102877.
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Functional Requirements for MLOps Systems utilized for the Simulation Component of Digital Twins
Rehberger, T. (2022). Functional Requirements for MLOps Systems utilized for the Simulation Component of Digital Twins. Master Thesis, University of Applied Sciences, Hagenberg. September 2022.
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Identification of Similarities and Clusters of Bread Baking Recipes Based on Data of Ingredients
Anlau, S., Lasslberger, M., Grassmann, R., Himmelbauer, J., & Winkler, S. (2022). Identification of Similarities and Clusters of Bread Baking Recipes Based on Data of Ingredients. Proceedings of the 8th International Food Operations and Processing Simulation Workshop (FoodOPS 2022).
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Plant recognition by AI: Deep neural nets, transformers, and kNN in deep embeddings
Picek, L., Šulc, M., Patel, Y., & Matas, J. (2022). Plant recognition by AI: Deep neural nets, transformers, and kNN in deep embeddings. Frontiers in Plant Science, 13.
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Quality Characteristics of a Software Platform for Human-AI Teaming in Smart Manufacturing
Haindl, P., Hoch, T., Dominguez, J., Aperribai, J., Ure, N. K., & Tunçel, M. (2022). Quality Characteristics of a Software Platform for Human-AI Teaming in Smart Manufacturing. Quality of Information and Communications Technology, 3–17.
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Recall@k Surrogate Loss with Large Batches and Similarity Mixup
Patel, Y., Tolias, G., & Matas, J. (2022). Recall@k Surrogate Loss with Large Batches and Similarity Mixup. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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Sustainable semantic similarity assessment
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2022). Sustainable semantic similarity assessment. Journal of Intelligent & Fuzzy Systems, 43(5), 6163–6174.
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Variational learning of deep fuzzy theoretic nonparametric model
Zhang, W., Kumar, M., Ding, W., Li, X., & Yu, J. (2022). Variational learning of deep fuzzy theoretic nonparametric model. Neurocomputing, 506, 128–145.
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11th International Conference, EGOVIS 2022, Vienna, Austria, August 22–24, 2022, Proceedings
Kő, A., Francesconi, E., Kotsis, G., Tjoa, A. M., & Khalil, I. (Eds.). (2022). Electronic Government and the Information Systems Perspective. Lecture Notes in Computer Science.
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24th International Conference, DaWaK 2022, Vienna, Austria, August 22–24, 2022, Proceedings
Wrembel, R., Gamper, J., Kotsis, G., Tjoa, A. M., & Khalil, I. (Eds.). (2022). Big Data Analytics and Knowledge Discovery. Lecture Notes in Computer Science.
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A Comparative Analysis of Anomaly Detection Methods for Predictive Maintenance in SME
Qasim, M., Khan, M., Mehmood, W., Sobieczky, F., Pichler, M., & Moser, B. (2022). A Comparative Analysis of Anomaly Detection Methods for Predictive Maintenance in SME. Database and Expert Systems Applications - DEXA 2022 Workshops, 22–31.
Zur Publikation -
A Scalable Microservice Infrastructure for Fleet Data Management
Meindl, R., Papesh, K., Baumgartner, D., & Helm, E. (2022). A Scalable Microservice Infrastructure for Fleet Data Management. Database and Expert Systems Applications - DEXA 2022 Workshops, 392–401.
Zur Publikation -
A Synthetic Dataset for Anomaly Detection of Machine Behavior
Luftensteiner, S., & Praher, P. (2022). A Synthetic Dataset for Anomaly Detection of Machine Behavior. Database and Expert Systems Applications - DEXA 2022 Workshops, 424–431.
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A Systematic Mapping Study of Predictive Maintenance in SMEs
Khan, M., Ahmad, A., Sobieczky, F., Pichler, M., Moser, B. A., & Bukovsky, I. (2022). A Systematic Mapping Study of Predictive Maintenance in SMEs. IEEE Access, 10, 88738–88749.
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An untold tale of scientific collaboration: SCCH and AC2T
Kargaran, S., Glock, A.-C., Freudenthaler, B., Freudenberger, M., & Jech, M. (2022). An Untold Tale of Scientific Collaboration: SCCH and AC$$^2$$T. Database and Expert Systems Applications - DEXA 2022 Workshops, 119–128.
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Applying Time-Inhomogeneous Markov Chains to Math Performance Rating
E.-M., Infanger, G., Lavicza, Z., & Sobieczky, F. (2022). Applying Time-Inhomogeneous Markov Chains to Math Performance Rating. Database and Expert Systems Applications - DEXA 2022 Workshops, 11–21.
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Challenges in Mass Flow Estimation on Conveyor Belts in the Mining Industry: A Case Study
Heinzl, B., Hinterreiter, C., Roßbory, M., & Hinterdorfer, C. (2022). Challenges in Mass Flow Estimation on Conveyor Belts in the Mining Industry: A Case Study. Database and Expert Systems Applications - DEXA 2022 Workshops, 90–99.
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Collaborative aspects of solving rail-track multi-sensor data fusion
Kromp, F., Hinterberger, F., Konanur, D., & Wieser, V. (2022). Collaborative Aspects of Solving Rail-Track Multi-sensor Data Fusion. Database and Expert Systems Applications - DEXA 2022 Workshops, 69–78.
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Data Integration, Management, and Quality: From Basic Research to Industrial Application
Ehrlinger, L., Lettner, C., Fragner, W., Gsellmann, G., Nestelberger, S., Rauchenzauner, F., Schützeneder, S., Tiefengrabner, M., & Zeindl, J. (2022). Data Integration, Management, and Quality: From Basic Research to Industrial Application. Database and Expert Systems Applications - DEXA 2022 Workshops, 167–178.
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Database and Expert Systems Applications - 33rd International Conference, DEXA 2022, Vienna, Austria, August 22–24, 2022, Proceedings, Part I
Strauss, C., Cuzzocrea, A., Kotsis, G., Tjoa, A. M., & Khalil, I. (Eds.). (2022). Database and Expert Systems Applications. Lecture Notes in Computer Science.
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Database and Expert Systems Applications - 33rd International Conference, DEXA 2022, Vienna, Austria, August 22–24, 2022, Proceedings, Part II
Strauss, C., Cuzzocrea, A., Kotsis, G., Tjoa, A. M., & Khalil, I. (Eds.). (2022). Database and Expert Systems Applications. Lecture Notes in Computer Science.
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Database and Expert Systems Applications - DEXA 2022 Workshops, 33rd International Conference, DEXA 2022, Vienna, Austria, August 22–24, 2022
Kotsis, G., Tjoa, A. M., Khalil, I., Moser, B., Taudes, A., Mashkoor, A., Sametinger, J., Martinez-Gil, J., Sobieczky, F., Fischer, L., Ramler, R., Khan, M., & Czech, G. (Eds.). (2022). Database and Expert Systems Applications - DEXA 2022 Workshops. Communications in Computer and Information Science.
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Deep Residual Policy Reinforcement Learning as a Corrective Term in Process Control for Alarm Reduction: A Preliminary Report
Abbas, A., Chasparis, G., & Kelleher, J. (2022). Deep Residual Policy Reinforcement Learning as a Corrective Term in Process Control for Alarm Reduction: A Preliminary Report. 2022 European Conference on Safety and Reliability (ESREL)
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Detection of the 3D Ground Plane from 2D Images for Distance Measurement to the Ground
Cakiroglu, O., Wieser, V., Zellinger, W., Souza Ribeiro, A., Kloihofer, W., & Kromp, F. (2022). Detection of the 3D Ground Plane from 2D Images for Distance Measurement to the Ground. Database and Expert Systems Applications - DEXA 2022 Workshops, 44–54.
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Does it Transfer? Assessing model generalization in domain adaptation with data fusion (Abstract)
Nikzad-Langerodi, R., & Fonseca Diaz, V. (2022) Does it Transfer? Assessing model generalization in domain adaptation with data fusion (Abstract). 18th Chemometrics in Analytical Chemistry Conference (CAC 2022)
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Enhancing TransE to Predict Process Behavior in Temporal Knowledge Graphs
Karetnikov, A., Ehrlinger, L., & Geist, V. (2022). Enhancing TransE to Predict Process Behavior in Temporal Knowledge Graphs. Database and Expert Systems Applications - DEXA 2022 Workshops, 369–374.
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Fast and Automatic Object Registration for Human-Robot Collaboration in Industrial Manufacturing
Geiß, M., Baresch, M., Chasparis, G., Schweiger, E., Teringl, N., & Zwick, M. (2022). Fast and Automatic Object Registration for Human-Robot Collaboration in Industrial Manufacturing. Database and Expert Systems Applications - DEXA 2022 Workshops, 232–242.
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From Data to Decisions - Developing Data Analytics Use-Cases in Process Industry
Himmelbauer, J., Mayr, M., & Luftensteiner, S. (2022). From Data to Decisions - Developing Data Analytics Use-Cases in Process Industry. Database and Expert Systems Applications - DEXA 2022 Workshops, 79–89.
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Interpretable Input-Output Hidden Markov Model- Based Deep Reinforcement Learning for the Predictive Maintenance of Turbofan Engines
Abbas, A. N., Chasparis, G. C., & Kelleher, J. D. (2022). Interpretable Input-Output Hidden Markov Model-Based Deep Reinforcement Learning for the Predictive Maintenance of Turbofan Engines. Lecture Notes in Computer Science, 133–148.
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Introduction of visual regression testing in collaboration between industry and academia
Wetzlmaier, T., Klammer, C., & Haslauer, H. (2022). Introduction of Visual Regression Testing in Collaboration Between Industry and Academia. Database and Expert Systems Applications - DEXA 2022 Workshops, 189–198.
Zur Publikation -
Log File Anomaly detection based on Process Mining Graphs
Luftensteiner, S., & Praher, P. (2022). Log File Anomaly Detection Based on Process Mining Graphs. Database and Expert Systems Applications - DEXA 2022 Workshops, 383–391.
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Matching Large Biomedical Ontologies Using Symbolic Regression -Extended Version-
Martinez-Gil, J., Yin, S., Kung, J., & Morvan, F. (2022). Matching Large Biomedical Ontologies Using Symbolic Regression Using Symbolic Regression. Journal of Data Intelligence, 3(3), 316–332.
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On the Creation and Maintenance of a Documentation Generator in an Applied Research Context
Dorninger, B., Moser, M., Pichler, J., Rappl, M., & Sautter, J. (2022). On the Creation and Maintenance of a Documentation Generator in an Applied Research Context. Database and Expert Systems Applications - DEXA 2022 Workshops, 129–140.
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Quantile time-frequency price connectedness between bond, green equity, sustainable investments and clean energy markets
Chatziantoniou, I., Abakah, E. J. A., Gabauer, D., & Tiwari, A. K. (2022). Quantile time–frequency price connectedness between green bond, green equity, sustainable investments and clean energy markets. Journal of Cleaner Production, 361, 132088.
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Simulation Paths for Quantum Circuit Simulation with Decision Diagrams
Burgholzer, L., Ploier, A., & Wille, R. (2023). Simulation Paths for Quantum Circuit Simulation With Decision Diagrams What to Learn From Tensor Networks, and What Not. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 42(4), 1113–1122.
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Synthetic Data in Automatic Number Plate Recognition
Brunner, D., & Schmid, F. (2022). Synthetic Data in Automatic Number Plate Recognition. Database and Expert Systems Applications - DEXA 2022 Workshops, 112–118.
Zur Publikation -
Time-Varying Predictability of Financial Stress on Inequality in United Kingdom
Berisha, E., Gabauer, D., Gupta, R., & Nel, J. (2022). Time-varying predictability of financial stress on inequality in United Kingdom. Journal of Economic Studies.
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Towards Practical Secure Privacy-Preserving Machine (Deep) Learning with Distributed Data
Kumar, M., Moser, B., Fischer, L., & Freudenthaler, B. (2022). Towards Practical Secure Privacy-Preserving Machine (Deep) Learning with Distributed Data. Database and Expert Systems Applications - DEXA 2022 Workshops, 55–66.
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Twenty Years of Successful Translational Research - A Case Study of Three COMET Centers
Bühler, K., Travniceck, C., Nowak, V., Weippl, E., Fischer, L., Ramler, R., & Wille, R. (2022). Twenty Years of Successful Translational Research: A Case Study of Three COMET Centers. Database and Expert Systems Applications - DEXA 2022 Workshops, 155–166.
Zur Publikation -
Unboundedness of Linear Regions of Deep ReLU Neural Networks.
Ponomarchuk, A., Koutschan, C., & Moser, B. (2022). Unboundedness of Linear Regions of Deep ReLU Neural Networks. Database and Expert Systems Applications - DEXA 2022 Workshops, 3–10.
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Using Property Graphs to Segment Time-Series Data
Karetnikov, A., Rehberger, T., Lettner, C., Himmelbauer, J., Nikzad-Langerodi, R., Gsellmann, G., Nestelberger, S., & Schützeneder, S. (2022). Using Property Graphs to Segment Time-Series Data. Database and Expert Systems Applications - DEXA 2022 Workshops, 416–423.
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Admission Certification for Digital Pilots in Public Traffic
Nessler, B., Fischer, L., Martinez-Gil, J., Holom, R.-M., Bosa, K., Kastner, K.-H., Tatschl-Unterberger, E., Watzinger, H., Weissenböck, J., Doms, T., & Schwald, C. (2022) Admission Certification for Digital Pilots in Public Traffic. IJCAI Workshop AI4AD
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Artificial intelligence algorithms reach expert-level accuracy in automated grading of blastocyst morphology assessment based on static embryo images and Gardner criteria
Kromp, F., Balaban, B., Cottin, V., Saiz, I. C., Fancsovits, P., Fawzy, M., Findikli, N., Kovacic, B., Ljiljak, D., Rodero, I. M., Parmegiani, L., Shebl, O., Wagner, R., Xie, M., & Ebner, T. (2022). O-285 Artificial intelligence algorithms reach expert-level accuracy in automated grading of blastocyst morphology assessment based on static embryo images and Gardner criteria. Human Reproduction, 37(Supplement_1).
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Characteristics of Reversible Circuits for Error Detection
Burgholzer, L., Wille, R., & Kueng, R. (2022). Characteristics of reversible circuits for error detection. Array, 14, 100165.
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Dynamic connectedness between COVID-19 news sentiment, capital and commodity markets
Apergis, N., Chatziantoniou, I., & Gabauer, D. (2022). Dynamic connectedness between COVID-19 news sentiment, capital and commodity markets. Applied Economics, 55(24), 2740–2754.
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Equivalence checking paradigms in quantum circuit design: A case study.
Peham, T., Burgholzer, L., & Wille, R. (2022). Equivalence checking paradigms in quantum circuit design. Proceedings of the 59th ACM/IEEE Design Automation Conference.
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FDG-PET combined with Learning Vector Quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder
van Veen, R., Meles, S. K., Renken, R. J., Reesink, F. E., Oertel, W. H., Janzen, A., de Vries, G.-J., Leenders, K. L., & Biehl, M. (2022). FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder. Computer Methods and Programs in Biomedicine, 225, 107042.
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Fuzzing and Delta Debugging And-Inverter Graph Verification Tools
Kaufmann, D., & Biere, A. (2022). Fuzzing and Delta Debugging And-Inverter Graph Verification Tools. Lecture Notes in Computer Science, 69–88.
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Reconciliation of Mental Concepts with Graph Neural Networks
Wendlinger, L., Hübscher, G., Ekelhart, A., & Granitzer, M. (2022). Reconciliation of Mental Concepts with Graph Neural Networks. Database and Expert Systems Applications, 133–146.
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Simulation of Pressure-Driven and Channel-Based Microfluidics on Different Abstract Levels: A Case Study
Takken, M., & Wille, R. (2022). Simulation of Pressure-Driven and Channel-Based Microfluidics on Different Abstract Levels: A Case Study. Sensors, 22(14), 5392.
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Tail risk connectedness in the refined petroleum market: A first look at the impact of the COVID-19 pandemic
Chatziantoniou, I., Gabauer, D., & Perez de Gracia, F. (2022). Tail risk connectedness in the refined petroleum market: A first look at the impact of the COVID-19 pandemic. Energy Economics, 111, 106051.
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Tessellation-Filtering ReLU Neural Networks
Moser, B. A., Lewandowski, M., Kargaran, S., Zellinger, W., Biggio, B., & Koutschan, C. (2022). Tessellation-Filtering ReLU Neural Networks. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.
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The Basis of Design Tools for Quantum Computing: Arrays, Decision Diagrams, Tensor Networks, ans ZX-Calculus.
Wille, R., Burgholzer, L., Hillmich, S., Grurl, T., Ploier, A., & Peham, T. (2022). The basis of design tools for quantum computing. Proceedings of the 59th ACM/IEEE Design Automation Conference.
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The Evolution of Monetary Policy Focal Points
Stenfors, A., Chatziantoniou, I., & Gabauer, D. (2022). The Evolution of Monetary Policy Focal Points. Journal of Economic Issues, 56(2), 348–355.
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Towards a SAT Encoding for Quantum Circuits: A Journey From Classical Circuits to Clifford Circuits and Beyond.
Berent, Lucas, Burgholzer, Lukas, & Wille, Robert. (2022). Towards a SAT Encoding for Quantum Circuits: A Journey From Classical Circuits to Clifford Circuits and Beyond. Schloss Dagstuhl - Leibniz-Zentrum Für Informatik.
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Channel Routing for Microfluidic Devices: A Comprehensive and Accessible Design Tool.
Ebner, P., Fink, G., & Wille, R. (2023). Channel Routing for Microfluidic Devices: A Comprehensive and Accessible Design Tool. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 42(2), 533–543.
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Handling Non-Unitaries in Quantum Circuit Equivalence Checking.
Burgholzer, L., & Wille, R. (2022). Handling non-unitaries in quantum circuit equivalence checking. Proceedings of the 59th ACM/IEEE Design Automation Conference.
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Noise-aware Quantum Circuit Simulation With Decision Diagrams.
Grurl, T., Fus, J., & Wille, R. (2023). Noise-Aware Quantum Circuit Simulation With Decision Diagrams. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 42(3), 860–873.
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A Comprehensive Survey on Electronic Design Automation and Graph Neural Networks: Theory and Applications. Transactions on Design Automation of Electronic Systems (TODAES).
Sánchez, D., Servadei, L., Kiprit, G. N., Wille, R., & Ecker, W. (2023). A Comprehensive Survey on Electronic Design Automation and Graph Neural Networks: Theory and Applications. ACM Transactions on Design Automation of Electronic Systems, 28(2), 1–27.
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Data Smells: Categories, Causes and Consequences, and Detection of Suspicious Data in AI-based Systems
Foidl, H., Felderer, M., & Ramler, R. (2022). Data smells. Proceedings of the 1st International Conference on AI Engineering: Software Engineering for AI.
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Dataset: Dependency Networks of Open Source Libraries Available Through CocoaPods, Carthage and Swift PM
Rahkema, K., & Pfahl, D. (2022). Dataset. Proceedings of the 19th International Conference on Mining Software Repositories.
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Evaluating PDDL for Programming Production Cells: a Case Study
Mayr-Dorn, C., Egyed, A., Winterer, M., Salomon, C., & Fürschuß, H. (2022). Evaluating PDDL for programming production cells. Proceedings of the 4th International Workshop on Robotics Software Engineering.
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Evolving software system families in space and time with feature revisions
Michelon, G. K., Obermann, D., Assunção, W. K. G., Linsbauer, L., Grünbacher, P., Fischer, S., Lopez-Herrejon, R. E., & Egyed, A. (2022). Evolving software system families in space and time with feature revisions. Empirical Software Engineering, 27(5).
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Graph-Based Managing and Mining of Processes and Data in the Domain of Intellectual Property
Hübscher, G., Geist, V., Auer, D., Ekelhart, A., Mayer, R., Nadschläger, S., & Küng, J. (2022). Graph-based managing and mining of processes and data in the domain of intellectual property. Information Systems, 106, 101844.
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Model-Driven Engineering of Safety and Security Software Systems: A Systematic Mapping Study and Future Research Directions.
Mashkoor, A., Egyed, A., Wille, R., & Stock, S. (2022). Model‐driven engineering of safety and security software systems: A systematic mapping study and future research directions. Journal of Software: Evolution and Process. Portico.
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SwiftDependencyChecker: Detecting Vulnerable Dependencies Declared Through CocoaPods, Carthage and Swift PM
Rahkema, K., & Pfahl, D. (2022). SwiftDependencyChecker. Proceedings of the 9th IEEE/ACM International Conference on Mobile Software Engineering and Systems.
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Towards a Reference Software Architecture for Human-AI Teaming in Smart Manufacturing
Haindl, P., Buchgeher, G., Khan, M., & Moser, B. (2022). Towards a Reference Software Architecture for Human-AI Teaming in Smart Manufacturing. 2022 IEEE/ACM 44th International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER).
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2D nnUNet for classification and segmentation of anatomical structures in fetal torso ultrasound
Dacho, C., Gabauer, D., Brunner, D., & Fischer, L. (2022). 2D nnUNet for classification and segmentation of anatomical structures in fetal torso ultrasound. Medical Imaging 2022: Image Processing.
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Design Automation for Continuous-Flow Lab-on-a-Chip Systems: A One-Pass Paradigm.
Huang, X., Pan, Y., Chen, Z., Guo, W., Wang, L., Li, Q., Wille, R., Ho, T.-Y., & Schlichtmann, U. (2023). Design Automation for Continuous-Flow Lab-on-a-Chip Systems: A One-Pass Paradigm. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 42(1), 327–331.
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Dual - and primal-constrained principal component analysis
Andries, E., & Nikzad‐Langerodi, R. (2022). Dual‐constrained and primal‐constrained principal component analysis. Journal of Chemometrics, 36(5). Portico.
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Neural Network Robustness Analysis Using Sensor Simulations for a Graphene-Based Semiconductor Gas Sensor
Schober, S. A., Bahri, Y., Carbonelli, C., & Wille, R. (2022). Neural Network Robustness Analysis Using Sensor Simulations for a Graphene-Based Semiconductor Gas Sensor. Chemosensors, 10(5), 152.
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Special Issue on Machine Learning and Knowledge Graphs
Alam, M., Fensel, A., Martinez-Gil, J., Moser, B., Recupero, D. R., & Sack, H. (2022). Special Issue on Machine Learning and Knowledge Graphs. Future Generation Computer Systems, 129, 50–53.
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A Replication Study on Predicting Metamorphic Relations at Unit Testing Level
Duque-Torres, A., Pfahl, D., Ramler, R., & Klammer, C. (2022). A Replication Study on Predicting Metamorphic Relations at Unit Testing Level. 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
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A Survey of Data Quality Measurement and Monitoring Tools
Ehrlinger, L., & Wöß, W. (2022). A Survey of Data Quality Measurement and Monitoring Tools. Frontiers in Big Data, 5.
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Abstracting Process Mining Event Logs From Process-State Data To Monitor Control-Flow Of Industrial Manufacturing Processes
Mayr, M., Luftensteiner, S., & Chasparis, G. C. (2022). Abstracting Process Mining Event Logs From Process-State Data To Monitor Control-Flow Of Industrial Manufacturing Processes. Procedia Computer Science, 200, 1442–1450.
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Artificial Intelligence and Software Engineering: Are We Ready?
Mashkoor, A., Menzies, T., Egyed, A., & Ramler, R. (2022). Artificial Intelligence and Software Engineering: Are We Ready? Computer, 55(3), 24–28.
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Automatic Design of Microfluidic Gradient Generators.
Fink, G., Mitteramskogler, T., Hintermuller, M. A., Jakoby, B., & Wille, R. (2022). Automatic Design of Microfluidic Gradient Generators. IEEE Access, 10, 28155–28164.
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Comprehensive and Accessible Channel Routing for Microfluidic Devices
Fink, G., Ebner, P., & Wille, R. (2022). Comprehensive and Accessible Channel Routing for Microfluidic Devices. 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE).
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Exploiting Arbitrary Paths for the Simulation of Quantum Circuits with Decision Diagrams
Burgholzer, L., Ploier, A., & Wille, R. (2022). Exploiting Arbitrary Paths for the Simulation of Quantum Circuits with Decision Diagrams. 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE).
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Generalized Input-Output Hidden-Markov-Models for Supervising Industrial Processes
Chasparis, G. C., Luftensteiner, S., & Mayr, M. (2022). Generalized Input-Output Hidden-Markov-Models for Supervising Industrial Processes. Procedia Computer Science, 200, 1402–1411.
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iTest: Using coverage measurements to improve test efficiency
Fischer, S., Rigoni, D., & Obrenovic, N. (2022). iTest: Using coverage measurements to improve test efficiency. 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
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Migrating Cyber-Physical Systems to OPC UA
Buchgeher, G., Dorninger, B., Klammer, C., Walchshofer, A., & Kern, A. (2022). Migrating Cyber-Physical Systems to OPC UA. Procedia Computer Science, 200, 276–283.
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Root Cause Analysis in the Industrial Domain using Knowledge Graphs: A Case Study on Power Transformers
Martinez-Gil, J., Buchgeher, G., Gabauer, D., Freudenthaler, B., Filipiak, D., & Fensel, A. (2022). Root Cause Analysis in the Industrial Domain using Knowledge Graphs: A Case Study on Power Transformers. Procedia Computer Science, 200, 944–953.
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Teaming.AI: Enabling Human-AI Teaming Intelligence in Manufacturing
Hoch, T., Heinzl, B., Czech, G., Khan, M., Waibel, P., Bachhofner, S., Kiesling, E., & Moser, B. A. (2022). Teaming.AI: Enabling Human-AI Teaming Intelligence in Manufacturing. International Conference on Interoperability for Enterprise Systems and Applications (I-ESA)
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Towards Attribute Grammar Mining by Symbolic Execution
Moser, M., Pichler, J., & Pointner, A. (2022). Towards Attribute Grammar Mining by Symbolic Execution. 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
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Using Source Code Metrics for Predicting Metamorphic Relations at Method Level
Duque-Torres, A., Pfahl, D., Klammer, C., & Fischer, S. (2022). Using Source Code Metrics for Predicting Metamorphic Relations at Method Level. 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
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What do we know about readability of test code? - A Systematic Mapping Study
Winkler, D., Urbanke, P., & Ramler, R. (2022). What Do We Know About Readability of Test Code? - A Systematic Mapping Study. 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
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Clinical data classification with noisy intermediate scale quantum computers.
Moradi, S., Brandner, C., Spielvogel, C., Krajnc, D., Hillmich, S., Wille, R., Drexler, W., & Papp, L. (2022). Clinical data classification with noisy intermediate scale quantum computers. Scientific Reports, 12(1).
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Comparing Automated Reuse of Scripted Tests and Model-Based Tests for Configurable Software
Fischer, S., Ramler, R., & Linsbauer, L. (2021). Comparing Automated Reuse of Scripted Tests and Model-Based Tests for Configurable Software. 2021 28th Asia-Pacific Software Engineering Conference (APSEC).
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Interpretable ontology meta-matching in the biomedical domain using Mamdani fuzzy inference
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2022). Interpretable ontology meta-matching in the biomedical domain using Mamdani fuzzy inference. Expert Systems with Applications, 188, 116025.
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The Role of Secondary Assists in Basketball – An analysis of its characteristics and effect on scoring
Supola, B., Hoch, T., & Baca, A. (2022). The role of secondary assists in basketball – an analysis of its characteristics and effect on scoring. International Journal of Performance Analysis in Sport, 22(2), 261–276.
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Tools for Quantum Computing Based on Decision Diagrams
Wille, R., Hillmich, S., & Burgholzer, L. (2022). Tools for Quantum Computing Based on Decision Diagrams. ACM Transactions on Quantum Computing, 3(3), 1–17.
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A Generic Sample Preparation Approach for Different Microfluidic Labs-on-Chips
Poddar, S., Fink, G., Haselmayr, W., & Wille, R. (2022). A Generic Sample Preparation Approach for Different Microfluidic Labs-on-Chips. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 41(11), 4612–4625.
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Deep Reinforcement Learning for Optimization at Early Design Stages.
Servadei, L., Lee, J. H., Arjona Medina, J. A., Werner, M., Hochreiter, S., Ecker, W., & Wille, R. (2023). Deep Reinforcement Learning for Optimization at Early Design Stages. IEEE Design & Test, 40(1), 43–51.
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Design Automation for Field-coupled Nanotechnologies.
Walter, M., Wille, R., Sill Torres, F., & Drechsler, R. (2022). Design Automation for Field-coupled Nanotechnologies.
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Improving the Robustness of Microfluidic Networks
Fink, G., Ebner, P., Poddar, S., & Wille, R. (2022). Improving the Robustness of Microfluidic Networks. 2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC).
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Limiting the Search Space in Optimal Quantum Circuit Mapping
Burgholzer, L., Schneider, S., & Wille, R. (2022). Limiting the Search Space in Optimal Quantum Circuit Mapping. 2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC).
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Deep Learning and Explainable Artificial Intelligence
Brucker, M. (2022). Deep Learning and Explainable Artificial Intelligence. Bachelor Thesis, University of Applied Sciences, Hagenberg
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2021
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An automated evaluation of broker compatibility for the Message Queuing Telemetry Transport protocol
Sochor, H., Ferrarotti, F., & Ramler, R. (2021). An automated evaluation of broker compatibility for the Message Queuing Telemetry Transport protocol. Journal of Software: Evolution and Process. Portico.
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Discrimination properties of binarized relu activations
Lewandowski, M., Zellinger, W., Eghbal-zadeh, H., Shepeleva, N., & Moser, B. A. (2023). On the Discriminability of Samples Using Binarized ReLU Activations. ICDSMLA 2021, 65–71.
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Matching Large Biomedical Ontologies Using Symbolic Regression
Martinez-Gil, J., Yin, S., Küng, J., & Morvan, F. (2021). Matching Large Biomedical Ontologies Using Symbolic Regression. The 23rd International Conference on Information Integration and Web Intelligence.
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On a regularization of unsupervised domain adaptation in RKHS
Gizewski, E. R., Mayer, L., Moser, B. A., Nguyen, D. H., Pereverzyev, S., Pereverzyev, S. V., Shepeleva, N., & Zellinger, W. (2022). On a regularization of unsupervised domain adaptation in RKHS. Applied and Computational Harmonic Analysis, 57, 201–227.
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Semantic similarity controllers: On the trade-off between accuracy and interpretability
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2021). Semantic similarity controllers: On the trade-off between accuracy and interpretability. Knowledge-Based Systems, 234, 107609.
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Test Benchmarks: Which One Now and in Future?
Artho, C., Benali, A., & Ramler, R. (2021). Test Benchmarks: Which One Now and in Future? 2021 IEEE 21st International Conference on Software Quality, Reliability and Security (QRS).
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The balancing principle for parameter choice in distance-regularized domain adaptation
Zellinger, W., Shepeleva, N., Dinu, M.-C., Eghbal-zadeh, H., Nguyen, H.D., Nessler, B., Pereverzyev, S.V., & Moser, B.A. (2021). The balancing principle for parameter choice in distance-regularized domain adaptation. Advances in neural Information Processing Systems 34 (NeurIPS 2021).
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BigIntegr: One-Pass Architectural Synthesis for Continuous-Flow Microfluidic Lab-on-a-Chip Systems
Huang, X., Pan, Y., Chen, Z., Guo, W., Wille, R., Ho, T.-Y., & Schlichtmann, U. (2021). BigIntegr: One-Pass Architectural Synthesis for Continuous-Flow Microfluidic Lab-on-a-Chip Systems. 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD).
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Evolution von Wissen, Aufgaben und Prozessen in einem 2D-Knowledge&Process-Graph
Hübscher, G., Auer, D., Geist, V., & Küng, J. (2021) Evolution von Wissen, Aufgaben und Prozessen in einem 2D-Knowledge&Process-Graph. ERP Future 2020 - Die Fachveranstaltung für Enterprise Systems in Österreich, 10. November 2020 in Hagenberg, Oberösterreich
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Is There an Association Between Bone Microarchitecture and Fracture in Patients who were Treated for High-grade Osteosarcoma? A Controlled Study at Long-term Follow-up Using High-resolution Peripheral Quantitative CT
Holzer, G., Hobusch, G., Hansen, S., Fischer, L., & Patsch, J. M. (2021). Is There an Association Between Bone Microarchitecture and Fracture in Patients who were Treated for High-grade Osteosarcoma? A Controlled Study at Long-term Follow-up Using High-resolution Peripheral Quantitative CT. Clinical Orthopaedics & Related Research, 479(11), 2493–2501.
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KI in der Praxis: Key Challenges im System-Engineering
Fischer, L., Ehrlinger, L., Geist, V., Ramler, R., Sobieczky, F., Zellinger, W., & Moser, B. (2021) KI in der Praxis: Key Challenges im System-Engineering. ERP Future 2020 - Die Fachveranstaltung für Enterprise Systems in Österreich, 10. November 2020 in Hagenberg, Oberösterreich
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Value-Oriented Quality Metrics in Software Development: Categorization and Practical Relevance from a Software Engineering Perspective
Haindl, P., & Plösch, R. (2021). Value‐oriented quality metrics in software development: Practical relevance from a software engineering perspective. IET Software, 16(2), 167–184. Portico.
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A Chemometrician's guide to Transfer Learning
Nikzad‐Langerodi, R., & Andries, E. (2021). A chemometrician’s guide to transfer learning. Journal of Chemometrics, 35(11). Portico.
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A logic for reflective ASMs
Schewe, K.-D., Ferrarotti, F., & González, S. (2021). A logic for reflective ASMs. Science of Computer Programming, 210, 102691.
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Are standard sample measurements still needed to transfer multivariate calibration models between near-infrared spectrometers? The answer is not always
Mishra, P., Nikzad-Langerodi, R., Marini, F., Roger, J. M., Biancolillo, A., Rutledge, D. N., & Lohumi, S. (2021). Are standard sample measurements still needed to transfer multivariate calibration models between near-infrared spectrometers? The answer is not always. TrAC Trends in Analytical Chemistry, 143, 116331.
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Crude Oil Futures Contracts and Commodity Markets: New Evidence from a TVP-VAR Extended Joint Connectedness Approach
Balcilar, M., Gabauer, D., & Umar, Z. (2021). Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach. Resources Policy, 73, 102219.
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Data-Driven Support of Coaches in Professional Cycling Using Race Performance Prediction
Karetnikov, A., Nuijten, W., & Hassani, M. (2021). Data-driven Support of Coaches in Professional Cycling using Race Performance Prediction. Proceedings of the 9th International Conference on Sport Sciences Research and Technology Support. doi:10.5220/0010656300003059
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Decision Diagrams for Quantum Measurements with Shallow Circuits
Hillmich, S., Hadfield, C., Raymond, R., Mezzacapo, A., & Wille, R. (2021). Decision Diagrams for Quantum Measurements with Shallow Circuits. 2021 IEEE International Conference on Quantum Computing and Engineering (QCE).
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Discovering DataOps: A Comprehensive Review of Definitions, Use Cases, and Tools
Mainali, K., Ehrlinger, L., Himmelbauer, J., & Matskin, M. (2021) Discovering DataOps: A Comprehensive Review of Definitions, Use Cases, and Tools. DATA ANALYTICS 2021 : The Tenth International Conference on Data Analytics, International Academy, Research, and Industry Association, pp. 61--69, 10-2021, ISBN: 978-1-61208-891-4.
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eknows: Platform for Multi-Language Reverse Engineering and Documentation Generation
Moser, M., & Pichler, J. (2021). eknows: Platform for Multi-Language Reverse Engineering and Documentation Generation. 2021 IEEE International Conference on Software Maintenance and Evolution (ICSME).
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Feature and Model Selection for Day-ahead Electricity-Load Forecasting in Residential Buildings
Kychkin, A. V., & Chasparis, G. C. (2021). Feature and model selection for day-ahead electricity-load forecasting in residential buildings. Energy and Buildings, 249, 111200.
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Hybrid Schrödinger-Feynman Simulation of Quantum Circuits With Decision Diagrams
Burgholzer, L., Bauer, H., & Wille, R. (2021). Hybrid Schrödinger-Feynman Simulation of Quantum Circuits With Decision Diagrams. 2021 IEEE International Conference on Quantum Computing and Engineering (QCE).
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IGA using Offset-based Overlapping Domain Parameterizations
Kargaran, S., Jüttler, B., & Takacs, T. (2021). IGA Using Offset-based Overlapping Domain Parameterizations. Computer-Aided Design, 139, 103087.
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Indirect Mass Flow Estimation based on Power Measurements of Conveyor Belts in Mineral Processing Applications
Heinzl, B., Martinez-Gil, J., Himmelbauer, J., Rosbory, M., Hinterdorfer, C., & Hinterreiter, C. (2021). Indirect Mass Flow Estimation based on Power Measurements of Conveyor Belts in Mineral Processing Applications. 2021 IEEE 19th International Conference on Industrial Informatics (INDIN).
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Time-varying spillovers between housing sentiment and housing market in the United States
André, C., Gabauer, D., & Gupta, R. (2021). Time-varying spillovers between housing sentiment and housing market in the United States☆. Finance Research Letters, 42, 101925.
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A brief note on application of domain-invariant PLS for adapting near-infrared spectroscopy calibrations between different physical forms of samples
Mishra, P., & Nikzad-Langerodi, R. (2021). A brief note on application of domain-invariant PLS for adapting near-infrared spectroscopy calibrations between different physical forms of samples. Talanta, 232, 122461.
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Adopting Microservices for Industrial Control Systems: A Five Step Migration Path
Buchgeher, G., Ramler, R., Stummer, H., & Kaufmann, H. (2021). Adopting Microservices for Industrial Control Systems: A Five Step Migration Path. 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ).
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Automated Test Case Generation using Interface Descriptions of the Industrial Communication Protocol OPC UA
Walchshofer, A. (2021). Automated Test Case Generation using Interface Descriptions of the Industrial Communication Protocol OPC UA. Master Thesis, University of Applied Sciences, Hagenberg. September 2021.
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Behavioural theory of reflective algorithms I: Reflective sequential algorithms
Schewe, K.-D., & Ferrarotti, F. (2022). Behavioural theory of reflective algorithms I: Reflective sequential algorithms. Science of Computer Programming, 223, 102864.
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Data Catalogs: A Systematic Literature Review and Steps to Implementation
Ehrlinger, L., Schrott, J., Melichar, M., Kirchmayr, N., & Wöß, W. (2021). Data Catalogs: A Systematic Literature Review and Guidelines to Implementation. Database and Expert Systems Applications - DEXA 2021 Workshops, 148–158.
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Deep Learning Rule for Efficient ChangepointDetection in the Presence of non-linear Trends
Mahmoud, S., Martinez-Gil, J., Praher, P., Freudenthaler, B., & Girkinger, A. (2021). Deep Learning Rule for Efficient Changepoint Detection in the Presence of Non-Linear Trends. Database and Expert Systems Applications - DEXA 2021 Workshops, 184–191.
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FEDS - Filtered Edit Distance Surrogate
Patel, Y., & Matas, J. (2021). FEDS - Filtered Edit Distance Surrogate. Lecture Notes in Computer Science, 171–186.
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Filter-based Feature Selection Methods for Industrial Sensor Data: A Review
Luftensteiner, S., Mayr, M., & Chasparis, G. (2021). Filter-Based Feature Selection Methods for Industrial Sensor Data: A Review. Lecture Notes in Computer Science, 242–249.
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Graph-based methods in multivariate calibration and calibration transfer (Abstract)
Nikzad-Langerodi, R., & Sobieczky, F. (2021). Graph-based methods in multivariate calibration and calibration transfer (Abstract). The great SCIentific eXchange (SCIX) 2021
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Interpretable entity meta-alignment in knowledge graphs using penalized regression: a case study in the biomedical domain
Martinez-Gil, J., Mokadem, R., Morvan, F., Küng, J., & Hameurlain, A. (2021). Interpretable entity meta-alignment in knowledge graphs using penalized regression: a case study in the biomedical domain. Progress in Artificial Intelligence, 11(1), 93–104.
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Knowledge Graph Embeddings for News Article Tag Recommendation
Engleitner, N., Kreiner, W., Schwarz, N., Kopetzky, T., & Ehrlinger, L. (2021) Knowledge Graph Embeddings for News Article Tag Recommendation. Joint Proceedings of the Semantics co-located events: Poster&Demo track and Workshop on Ontology-Driven Conceptual Modelling of Digital Twins, CEUR Workshop Proceedings, Vol. 2941, Sun SITE Central Europe, Aachen, 9-2021.
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Least resolved trees for two-colored best match graphs
Schaller, D., Geiß, M., Hellmuth, M., & Stadler, P. F. (2021). Least resolved trees for two-colored best match graphs. Journal of Graph Algorithms and Applications, 25(1), 397–416.
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Membership-Mappings for Data Representation Learning: A Bregman Divergence Based Conditionally Deep Autoencoder
Kumar, M., Moser, B., Fischer, L., & Freudenthaler, B. (2021). Membership-Mappings for Data Representation Learning: A Bregman Divergence Based Conditionally Deep Autoencoder. Database and Expert Systems Applications - DEXA 2021 Workshops, 138–147.
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Membership-Mappings for Data Representation Learning: Measure Theoretic Conceptualization
Kumar M., Moser B., Fischer L., Freudenthaler B. (2021) Membership-Mappings for Data Representation Learning: Measure Theoretic Conceptualization. Database and Expert Systems Applications - DEXA 2021 Workshops.
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Methods for Automatic Machine-Learning Workflow Analysis
Wendlinger, L., Berndl, E., & Granitzer, M. (2021). Methods for Automatic Machine-Learning Workflow Analysis. Lecture Notes in Computer Science, 52–67.
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Practical Assessment of Payload- Header Switching in Microfluidic Networks
Hamidović, M., Fink, G., Wille, R., Springer, A., & Haselmayr, W. (2021). Practical Assessment of Payload- Header Switching in Microfluidic Networks. Proceedings of the Eight Annual ACM International Conference on Nanoscale Computing and Communication.
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Quantum k-community detection: Algorithm proposals and cross-architectural evaluation
Gemeinhardt, F. G., Wille, R., & Wimmer, M. (2021). Quantum k-community detection: algorithm proposals and cross-architectural evaluation. Quantum Information Processing, 20(9).
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Representation and Presentation of Knowledge and Processes - An Integrated Approach for a Dynamic Communication-intensive Environment
Hübscher, G., Geist, V., Auer, D., Hübscher, N., & Küng, J. (2021). Representation and presentation of knowledge and processes – an integrated approach for a dynamic communication-intensive environment. International Journal of Web Information Systems, 17(6), 669–697.
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Robust and Efficient Bio-Inspired Data-Sampling Prototype for Time-Series Analysis
Lunglmayr, M., Lindorfer, G., & Moser, B. (2021). Robust and Efficient Bio-Inspired Data-Sampling Prototype for Time-Series Analysis. Database and Expert Systems Applications - DEXA 2021 Workshops, 119–126.
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Task-specific Automation in Deep Learning Processes
Buchgeher, G., Czech, G., Ribeiro, A. S., Kloihofer, W., Meloni, P., Busia, P., Deriu, G., Pintor, M., Biggio, B., Chesta, C., Rinelli, L., Solans, D., & Portela, M. (2021). Task-Specific Automation in Deep Learning Processes. Database and Expert Systems Applications - DEXA 2021 Workshops, 159–169.
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Towards a Stochastic Drift Simulation Model for Graphene-Based Gas Sensors
Schober, S. A., Carbonelli, C., Roth, A., Zoepfl, A., Travan, C., & Wille, R. (2022). Toward a Stochastic Drift Simulation Model for Graphene-Based Gas Sensors. IEEE Sensors Journal, 22(12), 11307–11316.
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Towards calibration transfer with arbitrary standards (Abstract)
Nikzad-Langerodi, R., & Sobieczky, F. (2021). Towards calibration transfer with arbitrary standards (Abstract). 17th Scandinavian Symposium on Chemometrics
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Accurate and Robust Malware Detection: Running XGBoost on Run-Time Data from Performance Counters
Elnaggar, R., Servadei, L., Mathur, S., Wille, R., Ecker, W., & Chakrabarty, K. (2022). Accurate and Robust Malware Detection: Running XGBoost on Runtime Data From Performance Counters. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 41(7), 2066–2079.
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Descriptive Complexity of Deterministic Polylogarithmic Time and Space
Ferrarotti, F., González, S., Turull Torres, J. M., Van den Bussche, J., & Virtema, J. (2021). Descriptive complexity of deterministic polylogarithmic time and space. Journal of Computer and System Sciences, 119, 145–163.
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Heuristic Algorithms for Best Match Graph Editing
Schaller, D., Geiß, M., Hellmuth, M., & Stadler, P. F. (2021). Heuristic algorithms for best match graph editing. Algorithms for Molecular Biology, 16(1).
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Integrating Usage Monitoring for Continuous Evaluation and Testing in the UI of an Industry Application
Fischer, S., Klammer, C., & Ramler, R. (2021). Integrating usage monitoring for continuous evaluation and testing in the UI of an industry application. Proceedings of the 12th International Workshop on Automating TEST Case Design, Selection, and Evaluation.
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Landscape of Bone Marrow Metastasis in Human Neuroblastoma Unraveled by Transcriptomics and Deep Multiplex Imaging
Lazic, D., Kromp, F., Rifatbegovic, F., Repiscak, P., Kirr, M., Mivalt, F., Halbritter, F., Bernkopf, M., Bileck, A., Ussowicz, M., Ambros, I. M., Ambros, P. F., Gerner, C., Ladenstein, R., Ostalecki, C., & Taschner-Mandl, S. (2021). Landscape of Bone Marrow Metastasis in Human Neuroblastoma Unraveled by Transcriptomics and Deep Multiplex Imaging. Cancers, 13(17), 4311.
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Missing Data Pattern: From Theory to an Application in the Steel Industry
Bechny, M., Sobieczky, F., Zeindl, J., & Ehrlinger, L. (2021). Missing Data Patterns: From Theory to an Application in the Steel Industry. 33rd International Conference on Scientific and Statistical Database Management.
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On the Dynamics of International Real-Estate-Investment Trust-Propagation Mechanisms: Evidence from Time-Varying Return and Volatility Connectedness Measuress
Lesame, K., Bouri, E., Gabauer, D., & Gupta, R. (2021). On the Dynamics of International Real-Estate-Investment Trust-Propagation Mechanisms: Evidence from Time-Varying Return and Volatility Connectedness Measures. Entropy, 23(8), 1048.
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Software-Qualitätssicherung im Maschinen- und Anlagenbau: automatisierte Bewertung der technischen Qualität von SPS Code
Dorninger, B., & Ziebermayr, T. (2021). Software-Qualitätssicherung im Maschinen- und Anlagenbau: automatisierte Bewertung der technischen Qualität von SPS-Code. E & i Elektrotechnik Und Informationstechnik, 138(6), 315–320.
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Advances and Challenges for Model and Data Engineering (editorial)
Attiogbé, C., Ferrarotti, F., & Maabout, S. (2021). Advances and Challenges for Model and Data Engineering. JUCS - Journal of Universal Computer Science, 27(7), 646–649.
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As Accurate as Needed, as Efficient as Possible: Approximations in DD-based Quantum Circuit Simulation
Hillmich, S., Kueng, R., Markov, I. L., & Wille, R. (2021). As Accurate as Needed, as Efficient as Possible: Approximations in DD-based Quantum Circuit Simulation. 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE).
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Auswirkungen von DRAM-Timings auf die Effektivität von Rowhammer-Attacken
Fischer, B. (2021). Auswirkungen von DRAM-Timings auf die Effektivität von Rowhammer-Attacken. Bachelor Thesis; Fachhochschule Hagenberg. July 2021.
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DQ-MeeRKat: Automating Data Quality Monitoring with a Reference-Data-Profile-Annotated Knowledge Graph
Ehrlinger, L., Gindlhumer, A., Huber, L.-M., & Wöß, W. (2021). DQ-MeeRKat: Automating Data Quality Monitoring with a Reference-Data-Profile-Annotated Knowledge Graph. Proceedings of the 10th International Conference on Data Science, Technology and Applications.
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Evaluation of Deep Learning architectures for complex immunofluorescence nuclear image segmentation
Kromp, F., Fischer, L., Bozsaky, E., Ambros, I. M., Dorr, W., Beiske, K., Ambros, P. F., Hanbury, A., & Taschner-Mandl, S. (2021). Evaluation of Deep Learning Architectures for Complex Immunofluorescence Nuclear Image Segmentation. IEEE Transactions on Medical Imaging, 40(7), 1934–1949.
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Exact Physical Design of Quantum Circuits for Ion-Trap-based Quantum Architectures
Keszocze, O., Mohammadzadeh, N., & Wille, R. (2021). Exact Physical Design of Quantum Circuits for Ion-Trap-based Quantum Architectures. 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE).
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Generic Sample Preparation for Different Microfluidic Platforms
Poddar, S., Fink, G., Haselmayr, W., & Wille, R. (2021). Generic Sample Preparation for Different Microfluidic Platforms. 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE).
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On the truncated Hausdorff moment problem under Sobolev regularity conditions
Zellinger, W., & Moser, B. A. (2021). On the truncated Hausdorff moment problem under Sobolev regularity conditions. Applied Mathematics and Computation, 400, 126057.
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Stochastic Quantum Circuit Simulation Using Decision Diagrams
Grurl, T., Kueng, R., FuB, J., & Wille, R. (2021). Stochastic Quantum Circuit Simulation Using Decision Diagrams. 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE).
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Towards Automatic Design and Verification for Level 3 of the European Train Control System
Wille, R., Peham, T., Przigoda, J., & Przigoda, N. (2021). Towards Automatic Design and Verification for Level 3 of the European Train Control System. 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE).
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Visualizing Decision Diagrams for Quantum Computing
Wille, R., Burgholzer, L., & Artner, M. (2021). Visualizing Decision Diagrams for Quantum Computing (Special Session Summary). 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE).
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ASM Specification and Refinement of a Quantum Algorithm
Ferrarotti, F., & González, S. (2021). ASM Specification and Refinement of a Quantum Algorithm. Lecture Notes in Computer Science, 135–146.
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AVUBDI: A Versatile Usable Big Data Infrastructure and its Monitoring Approaches for Process Industry
Luftensteiner, S., Mayr, M., Chasparis, G. C., & Pichler, M. (2021). AVUBDI: A Versatile Usable Big Data Infrastructure and Its Monitoring Approaches for Process Industry. Frontiers in Chemical Engineering, 3.
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Considerations for using Block-Based Languages for Industrial Robot Programming - a Case Study
Mayr-Dorn, C., Winterer, M., Salomon, C., Hohensinger, D., & Ramler, R. (2021). Considerations for using Block-Based Languages for Industrial Robot Programming - a Case Study. 2021 IEEE/ACM 3rd International Workshop on Robotics Software Engineering (RoSE).
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Dynamic Connectedness And Spillovers Across Sectors: Evidence From The Indian Stock Market
Chatziantoniou, I., Gabauer, D., & Marfatia, H. A. (2021). Dynamic connectedness and spillovers across sectors: Evidence from the Indian stock market. Scottish Journal of Political Economy, 69(3), 283–300. Portico.
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Dynamic Measures of Asymmetric & Pairwise Spillovers within an Optimal Currency Area: Evidence from the ERM I System
Gabauer, D. (2021). Dynamic measures of asymmetric & pairwise connectedness within an optimal currency area: Evidence from the ERM I system. Journal of Multinational Financial Management, 60, 100680.
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Efficient Construction of Functional Representations for Quantum Algorithms
Burgholzer, L., Raymond, R., Sengupta, I., & Wille, R. (2021). Efficient Construction of Functional Representations for Quantum Algorithms. Lecture Notes in Computer Science, 227–241.
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Extended Authorization Policy for Graph-Structured Data
Mohamed, A., Auer, D., Hofer, D., & Küng, J. (2021). Extended Authorization Policy for Graph-Structured Data. SN Computer Science, 2(5).
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GraphifyEvolution - A Modular Approach to Analysing Source Code Histories
Rahkema, K., & Pfahl, D. (2021). GraphifyEvolution - A Modular Approach to Analysing Source Code Histories. 2021 IEEE/ACM 8th International Conference on Mobile Software Engineering and Systems (MobileSoft).
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MAD: Memory Allocation meets Software Diversity
Wiesinger, M., Dorfmeister, D., & Brunthaler S. (2021) MAD: Memory Allocation meets Software Diversity. First Workshop on DRAM Security (DRAMSec), Co-located with ISCA 2021
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QCL-based mid-infrared hyperspectral imaging of multilayer polymer oxygen barrier-films
Zimmerleiter, R., Nikzad-Langerodi, R., Ruckebusch, C., Godejohann, M., Kilgus, J., Duswald, K., & Brandstetter, M. (2021). QCL-based mid-infrared hyperspectral imaging of multilayer polymer oxygen barrier-films. Polymer Testing, 98, 107190.
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Volatility connectedness of major cryptocurrencies: The role of investor happiness
Bouri, E., Gabauer, D., Gupta, R., & Tiwari, A. K. (2021). Volatility connectedness of major cryptocurrencies: The role of investor happiness. Journal of Behavioral and Experimental Finance, 30, 100463.
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A Case Study on the Evolution of Configuration Options of a Highly-Configurable Software System
Fischer, S. (2021). A Case Study on the Evolution of Configuration Options of a Highly-Configurable Software System. 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
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A Framework for Improving Offline Learning Models with Online Data
Luftensteiner, S., & Zwick, M. (2021) A Framework for Improving Offline Learning Models with Online Data. The Thirteen International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2021)
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Automated Continuous Data Quality Measurement
Ehrlinger L. (2021) Automated Continuous Data Quality Measurement. PhD Thesis, Johannes Kepler University Linz, May 2021.
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Best Match Graphs with Binary Trees
Schaller, D., Geiß, M., Hellmuth, M., & Stadler, P. F. (2021). Best Match Graphs with Binary Trees. Lecture Notes in Computer Science, 82–93.
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Interest Rate Swaps and the Transmission Mechanism of Monetary Policy: A Quantile Connectedness Approach
Chatziantoniou, I., Gabauer, D., & Stenfors, A. (2021). Interest rate swaps and the transmission mechanism of monetary policy: A quantile connectedness approach. Economics Letters, 204, 109891.
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Lessons Learnt in the Implementation of Quantum Circuit Simulation Using Decision Diagrams
Grurl, T., Fub, J., & Wille, R. (2021). Lessons Learnt in the Implementation of Quantum Circuit Simulation Using Decision Diagrams. 2021 IEEE 51st International Symposium on Multiple-Valued Logic (ISMVL).
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Modeling extra-deep EM logs using a deep neural network
Alyaev, S., Shahriari, M., Pardo, D., Omella, Á. J., Larsen, D. S., Jahani, N., & Suter, E. (2021). Modeling extra-deep electromagnetic logs using a deep neural network. GEOPHYSICS, 86(3), E269–E281.
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Simulating Defects in Environmental Sensor Networks Using Stochastic Sensor Models
Schober, S. A., Carbonelli, C., & Wille, R. (2021). Simulating Defects in Environmental Sensor Networks Using Stochastic Sensor Models. The 8th International Symposium on Sensor Science.
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Visualization of Multi-Level Data Quality Dimensions with QuaIIe
Martinez, S. I., Ehrlinger, L., & Wöß W. Visualization of Multi-Level Data Quality Dimensions with QuaIIe. DBKDA 2021, The Thirteenth International Conference on Advances in Databases, Knowledge, and Data Applications, International Academy, Research, and Industry Association, Seite(n) 15-20, 5-2021, ISBN: 978-1-61208-857-0
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A Swept Source Optical Coherence Tomography Angiography Study: Imaging artifacts and comparison of non-perfusion areas with fluorescein angiography in diabetic macular edema
Podkowinski, D., Beka, S., Mursch-Edlmayr, A.-S., Strauss, R. W., Fischer, L., & Bolz, M. (2021). A Swept source optical coherence tomography angiography study: Imaging artifacts and comparison of non-perfusion areas with fluorescein angiography in diabetic macular edema. PLOS ONE, 16(4), e0249918.
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Adaptive Sparse Cyclic Coordinate Descent for Sparse Frequency Estimation
Garcia Guzman, Y. E., & Lunglmayr, M. (2021). Adaptive Sparse Cyclic Coordinate Descent for Sparse Frequency Estimation. Signals, 2(2), 189–200.
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Efficient One-Pass Synthesis for Digital Microfluidic Biochips
Mohammadzadeh, N., Wille, R., & Keszocze, O. (2021). Efficient One-pass Synthesis for Digital Microfluidic Biochips. ACM Transactions on Design Automation of Electronic Systems, 26(4), 1–21.
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Financial market connectedness: The role of investors' happiness
Bouri, E., Demirer, R., Gabauer, D., & Gupta, R. (2022). Financial market connectedness: The role of investors’ happiness. Finance Research Letters, 44, 102075.
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Gaussian fuzzy theoretic analysis for variational learning of nested compositions
Kumar, M., Singh, S., & Freudenthaler, B. (2021). Gaussian fuzzy theoretic analysis for variational learning of nested compositions. International Journal of Approximate Reasoning, 131, 1–29.
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Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review
Buchgeher, G., Gabauer, D., Martinez-Gil, J., & Ehrlinger, L. (2021) Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review. IEEE Access, vol. 9, pp. 55537-55554.
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Monetary policy and speculative spillovers in financial markets
Demirer, R., Gabauer, D., Gupta, R., & Ji, Q. (2021). Monetary policy and speculative spillovers in financial markets. Research in International Business and Finance, 56, 101373.
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SMT-Based Placement for System-on-Chip Design
Pointner, S., Wenzek, S., & Wille, R. (2021). SMT-Based Placement for System-on-Chip Design. 2021 IEEE International Symposium on Circuits and Systems (ISCAS).
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A closer look into the global determinants of oil price volatility
Chatziantoniou, I., Filippidis, M., Filis, G., & Gabauer, D. (2021). A closer look into the global determinants of oil price volatility. Energy Economics, 95, 105092.
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Arc-Completion of 2-Colored Best Match Graphs to Binary-Explainable
Schaller, D., Geiß, M., Hellmuth, M., & Stadler, P. F. (2021). Arc-Completion of 2-Colored Best Match Graphs to Binary-Explainable Best Match Graphs. Algorithms, 14(4), 110.
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High Cortico-Trabecular Transitional Zone Porosity and Reduced Trabecular Density in Men and Women with Stress Fractures
Zendeli, A., Bui, M., Fischer, L., Ghasem-Zadeh, A., Schima, W., & Seeman, E. (2021). High Cortico-Trabecular Transitional Zone Porosity and Reduced Trabecular Density in Men and Women with Stress Fractures. Journal of Clinical Medicine, 10(5), 1123.
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Safe and secure cyber-physical systems
Biró, M., Mashkoor, A., & Sametinger, J. (2021). Safe and secure cyber‐physical systems. Journal of Software: Evolution and Process, 33(9). Portico.
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A Hybrid Feature Location Technique for Re-Engineering Single Systems into Software Product Lines
Michelon, G. K., Linsbauer, L., Assunção, W. K. G., Fischer, S., & Egyed, A. (2021). A Hybrid Feature Location Technique for Re-engineeringSingle Systems into Software Product Lines. Proceedings of the 15th International Working Conference on Variability Modelling of Software-Intensive Systems.
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Automated Reuse of Test Cases for Highly Configurable Software Systems
Fischer, S., Michelon, G. K., Ramler, R. R., Linsbauer, L. & Egyed, A., (2021). Automated Reuse of Test Cases for Highly Configurable Software Systems. In: Koziolek, A., Schaefer, I. & Seidl, C. (Hrsg.), Software Engineering 2021. Bonn: Gesellschaft für Informatik e.V.. (S. 39-40).
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Beyond Federated Learning: On Confidentiality-Critical Machine Learning Applications in Industry
Zellinger, W., Wieser, V., Kumar, M., Brunner, D., Shepeleva, N., Gálvez, R., Langer, J., Fischer, L., & Moser, B. (2021). Beyond federated learning: On confidentiality-critical machine learning applications in industry. Procedia Computer Science, 180, 734–743.
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Complete Characterization of Incorrect Orthology Assignments in Best Match Graphs
Schaller, D., Geiß, M., Stadler, P. F., & Hellmuth, M. (2021). Complete Characterization of Incorrect Orthology Assignments in Best Match Graphs. Journal of Mathematical Biology, 82(3).
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DaQL 2.0: Measure Data Quality based on Entity Models
Lettner, C., Stumptner, R., Fragner, W., Rauchenzauner, F., & Ehrlinger, L. (2021). DaQL 2.0: Measure Data Quality based on Entity Models. Procedia Computer Science, 180, 772–777.
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Decay-parameter Diagnosis in Industrial Domains by Robustness through Isotonic Regression
Mahmoud, S., Sobieczky, F., Martinez-Gil, J., Praher, P., & Freudenthaler, B. (2021). Decay-parameter Diagnosis in Industrial Domains by Robustness through Isotonic Regression. Procedia Computer Science, 180, 466–475.
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EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness
Chatziantoniou, I., & Gabauer, D. (2021). EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness. The Quarterly Review of Economics and Finance, 79, 1–14.
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Explainability of AI-predictions based on psychological profiling
Neugebauer, S., Rippitsch, L., Sobieczky, F., & Geiβ, M. (2021). Explainability of AI-predictions based on psychological profiling. Procedia Computer Science, 180, 1003–1012.
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Explaining a random forest with the difference of two Arima models in an industrial fault detection scenario
Glock, A.-C. (2021). Explaining a Random Forest With the Difference of Two ARIMA Models in an Industrial Fault Detection Scenario. Procedia Computer Science, 180, 476–481.
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Performance Aspects of Correctness-oriented Synthesis Flows
Bornebusch, F., Lüth, C., Wille, R., & Drechsler, R. (2021). Performance Aspects of Correctness-oriented Synthesis Flows. Proceedings of the 9th International Conference on Model-Driven Engineering and Software Development.
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Protecting Intellectual Property Rights of Industrial Software
Ziebermayr, T. (2021). Protecting Intellectual Property Rights of Industrial Software. Procedia Computer Science, 180, 862–866.
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QCEC: A JKQ Tool for Quantum Circuit Equivalence Checking
Burgholzer, L., & Wille, R. (2021). QCEC: A JKQ tool for quantum circuit equivalence checking. Software Impacts, 7, 100051.
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Testing of Highly Configurable Cyber-Physical Systems – A Multiple Case Study
Fischer, S., Ramler, R., Klammer, C., & Rabiser, R. (2021). Testing of Highly Configurable Cyber-Physical Systems – A Multiple Case Study. Proceedings of the 15th International Working Conference on Variability Modelling of Software-Intensive Systems.
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Time-Varying Predictability of Labor Productivity on Inequality in United Kingdom
Gabauer, D., Gupta, R., Nel, J., & Yamaka, W. (2021). Time-Varying Predictability of Labor Productivity on Inequality in United Kingdom. Social Indicators Research, 155(3), 771–788.
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Accurate and Efficient Simulation of Microfluidic Networks
Fink, G., Ebner, P., Hamidović, M., Haselmayr, W., & Wille, R. (2021). Accurate and Efficient Simulation of Microfluidic Networks. Proceedings of the 26th Asia and South Pacific Design Automation Conference.
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Exploiting Quantum Teleportation in Quantum Circuit Mapping
Hillmich, S., Zulehner, A., & Wille, R. (2021). Exploiting Quantum Teleportation in Quantum Circuit Mapping. Proceedings of the 26th Asia and South Pacific Design Automation Conference.
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One-Pass Synthesis for Field-coupled Nanocomputing Technologies
Walter, M., Haaswijk, W., Wille, R., Torres, F. S., & Drechsler, R. (2021). One-pass Synthesis for Field-coupled Nanocomputing Technologies. Proceedings of the 26th Asia and South Pacific Design Automation Conference.
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Quality Assurance for AI-based Systems: Overview and Challenges
Felderer, M., & Ramler, R. (2021). Quality Assurance for AI-Based Systems: Overview and Challenges (Introduction to Interactive Session). Lecture Notes in Business Information Processing, 33–42.
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Random Stimuli Generation for the Verification of Quantum Circuits
Burgholzer, L., Kueng, R., & Wille, R. (2021). Random Stimuli Generation for the Verification of Quantum Circuits. Proceedings of the 26th Asia and South Pacific Design Automation Conference.
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Testing autogenerated OPC UA NodeSet models for product variants in industry
Klammer, C., Wetzlmaier, T., Pfeiffer, M., Steiner, T., & Konnerth, M. (2021). Testing Autogenerated OPC UA NodeSet Models for Product Variants in Industry. Lecture Notes in Business Information Processing, 15–29.
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A Novel Neurofuzzy Approach for Semantic Similarity Measurement
Martinez-Gil, J., Mokadem, R., Küng, J., & Hameurlain, A. (2021). A Novel Neurofuzzy Approach for Semantic Similarity Measurement. Lecture Notes in Computer Science, 192–203.
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Design of borehole resistivity measurement acquisition systems using deep learning
Shahriari, M., Hazra, A., & Pardo, D. (2022). A deep learning approach to design a borehole instrument for geosteering. GEOPHYSICS, 87(2), D83–D90.
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Green Bond, Renewable Energy Stocks and Carbon Price: Dynamic Connectedness, Hedging and Investment Strategies during COVID-19 pandemic
Tiwari, A. K., Aikins Abakah, E. J., Gabauer, D., & Dwumfour, R. A. (2021). Green Bond, Renewable Energy Stocks and Carbon Price: Dynamic Connectedness, Hedging and Investment Strategies during COVID-19 pandemic. SSRN Electronic Journal. doi:10.2139/ssrn.3897284
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Hierarchical and Modularly-Minimal Vertex Colorings
Valdivia, D. I., Rosales, M. H., Geiß, M., Stadler, P. F., & Hellmuth, M. (2022). Hierarchical and modularly-minimal vertex colorings. The Art of Discrete and Applied Mathematics, 6(2), #P2.01.
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Return connectedness across asset classes around the COVID-19 outbreak
Bouri, E., Cepni, O., Gabauer, D., & Gupta, R. (2021). Return connectedness across asset classes around the COVID-19 outbreak. International Review of Financial Analysis, 73, 101646.
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Steering Drivers of Change: Maximising Benefits of Trustworthy IoT
Veledar, O., Armengaud, E., Botler, L. H., Damjanovic-Behrendt, V., Derler, C., Jaksic, S., Krammer, L., Lettner, C., Macher, G., Marksteiner, S., Martin, A., Matschnig, M., Priller, P., Ramacher, S., Römer, K., Schmittner, C., Tiefnig, C., Vallant, H., Weiskirchner, H., & Drobics, M. (2021). Steering Drivers of Change: Maximising Benefits of Trustworthy IoT. Systems, Software and Services Process Improvement, 663–674.
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Time-varying influence of household debt on inequality in the United Kingdom
Berisha, E., Gabauer, D., Gupta, R., & Lau, C. K. M. (2020). Time-varying influence of household debt on inequality in United Kingdom. Empirical Economics, 61(4), 1917–1933.
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Towards Reusable Ontology Alignment for Manufacturing Maintenance
Kainzner, M., Klösch, C., Filipiak, D., Chhetri, T. R., Fensel, A., & Martinez-Gil, J. (2021) Towards Reusable Ontology Alignment for Manufacturing Maintenance. SEMANTiCS.
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Traffic detection for the intersection case in Connecting Austria
Hoch, T., & Kopetzky, T. (2022). Energy-Efficient Internet of Things Solution for Traffic Monitoring. Lecture Notes in Intelligent Transportation and Infrastructure, 129–141.
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Uncertainty and forecastability of regional output growth in the United Kingdom: Evidence from Machine Learning
Balcilar, M., Gabauer, D., Gupta, R., & Pierdzioch, C. (2022). Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning. Journal of Forecasting, 41(6), 1049–1064. Portico.
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Uncertainty Quantification on the Inversion of Geosteering Measurements using Deep Learning
Rivera, J. A., Rivera, J. A., Pardo, D., Omella, J., & Torres-Verdín, C. (2021). Uncertainty Quantification on the Inversion of Geosteering Measurements using Deep Learning. 3rd EAGE/SPE Geosteering Workshop.
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2020
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A novel method based on symbolic regression for interpretable semantic similarity measurement
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2020). A novel method based on symbolic regression for interpretable semantic similarity measurement. Expert Systems with Applications, 160, 113663.
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AI System Engineering - Key Challenges and Lessons Learned
Fischer, L., Ehrlinger, L., Geist, V., Ramler, R., Sobiezky, F., Zellinger, W., Brunner, D., Kumar, M., & Moser, B. (2020). AI System Engineering—Key Challenges and Lessons Learned. Machine Learning and Knowledge Extraction, 3(1), 56–83.
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Domain adaptation for regression under Beer–Lambert’s law
Nikzad-Langerodi, R., Zellinger, W., Saminger-Platz, S., & Moser, B. A. (2020). Domain adaptation for regression under Beer–Lambert’s law. Knowledge-Based Systems, 210, 106447.
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Partial least square regression versus domain invariant partial least square regression with application to near-infrared spectroscopy of fresh fruit
Mishra, P., & Nikzad-Langerodi, R. (2020). Partial least square regression versus domain invariant partial least square regression with application to near-infrared spectroscopy of fresh fruit. Infrared Physics & Technology, 111, 103547.
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Using Rule Mining for Automatic Test Oracle Generation
Duque-Torres, A., Pfahl, D., Shalygina, A., & Ramler, R. (2020). Using Rule Mining for Automatic Test Oracle Generation. Proceedings of the 8th International Workshop on Quantitative Approaches to Software Quality co-located with 27th Asia-Pacific Software Engineering Conference (APSEC 2020), pages 21-28, ceur-ws.org, December 2020.
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Automatic compiler optimization on embedded software through k-means clustering
Werner, M., Servadei, L., Wille, R., & Ecker, W. (2020). Automatic compiler optimization on embedded software through k-means clustering. Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD.
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Considering decoherence errors in the simulation of quantum circuits using decision diagrams
Grurl, T., Fuß, J., & Wille, R. (2020). Considering decoherence errors in the simulation of quantum circuits using decision diagrams. Proceedings of the 39th International Conference on Computer-Aided Design.
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Cost Optimization at Early Stages of Design Using Deep Reinforcement Learning
Servadei, L., Zheng, J., Arjona-Medina, J., Werner, M., Esen, V., Hochreiter, S., Ecker, W., & Wille, R. (2020). Cost Optimization at Early Stages of Design Using Deep Reinforcement Learning. Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD.
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Current perspectives on the software engineering process (Editorial)
Biró, M., Colomo‐Palacios, R., & Messnarz, R. (2020). Current perspectives on the software engineering process. Journal of Software: Evolution and Process, 32(11). Portico.
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Error control and loss functions for the deep learning inversion of borehole resistivity measurements
Shahriari, M., Pardo, D., Rivera, J. A., Torres‐Verdín, C., Picon, A., Del Ser, J., Ossandón, S., & Calo, V. M. (2021). Error control and loss functions for the deep learning inversion of borehole resistivity measurements. International Journal for Numerical Methods in Engineering, 122(6), 1629–1657. Portico.
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Graph‐based calibration transfer
Nikzad‐Langerodi, R., & Sobieczky, F. (2020). Graph‐based calibration transfer. Journal of Chemometrics, 35(4). Portico.
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Integration of knowledge and task management in an evolving, communication-intensive
Hübscher, G., Geist, V., Auer, D., Hübscher, N., & Küng, J. (2020). Integration of Knowledge and Task Management in an Evolving, Communication-intensive Environment. Proceedings of the 22nd International Conference on Information Integration and Web-Based Applications & Services.
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JKQ: JKU tools for quantum computing
Wille, R., Hillmich, S., & Burgholzer, L. (2020). JKQ. Proceedings of the 39th International Conference on Computer-Aided Design.
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Leveraging machine learning for software redocumentation – A eomprehensive comparison of methods in practice
Geist, V., Moser, M., Pichler, J., Santos, R., & Wieser, V. (2020). Leveraging machine learning for software redocumentation—A comprehensive comparison of methods in practice. Software: Practice and Experience, 51(4), 798–823. Portico.
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On generalization in moment-based domain adaptation
Zellinger, W., Moser, B. A., & Saminger-Platz, S. (2020). On generalization in moment-based domain adaptation. Annals of Mathematics and Artificial Intelligence, 89(3–4), 333–369.
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Verifying results of the IBM Qiskit quantum circuit compilation flow
Burgholzer, L., Raymond, R., & Wille, R. (2020). Verifying Results of the IBM Qiskit Quantum Circuit Compilation Flow. 2020 IEEE International Conference on Quantum Computing and Engineering (QCE).
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Advanced Equivalence Checking for Quantum Circuits
Burgholzer, L., & Wille, R. (2021). Advanced Equivalence Checking for Quantum Circuits. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 40(9), 1810–1824.
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An expert review on the applicability of blockly for industrial robot programming
Winterer, M., Salomon, C., Koberle, J., Ramler, R., & Schittengruber, M. (2020). An Expert Review on the Applicability of Blockly for Industrial Robot Programming. 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA).
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An explainable fuzzy theoretic nonparametric deep model for stress assessment using heartbeat intervals analysis
Kumar, M., Zhang, W., Weippert, M., & Freudenthaler, B. (2021). An Explainable Fuzzy Theoretic Nonparametric Deep Model for Stress Assessment Using Heartbeat Intervals Analysis. IEEE Transactions on Fuzzy Systems, 29(12), 3873–3886.
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Exploring the Potential Benefits of Alternative Quantum Computing Architectures
Deb, A., Dueck, G. W., & Wille, R. (2021). Exploring the Potential Benefits of Alternative Quantum Computing Architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 40(9), 1825–1835.
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Image matching across wide baselines: From paper to practice
Jin, Y., Mishkin, D., Mishchuk, A., Matas, J., Fua, P., Yi, K. M., & Trulls, E. (2020). Image Matching Across Wide Baselines: From Paper to Practice. International Journal of Computer Vision, 129(2), 517–547.
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Stepwise abstraction of high-level system specifications from source code
Ferrarotti, F., Moser, M., & Pichler, J. (2020). Stepwise abstraction of high-level system specifications from source code. Journal of Computer Languages, 60, 100996.
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Towards drift modeling of graphene-based gas sensors using stochastic simulation techniques
Schober, S. A., Carbonelli, C., Roth, A., Zoepfl, A., & Wille, R. (2020). Towards Drift Modeling of Graphene-Based Gas Sensors Using Stochastic Simulation Techniques. 2020 IEEE SENSORS.
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Towards optimal assembly line order sequencing with reinforcement learning: A case study
Shafiq, S., Mayr-Dorn, C., Mashkoor, A., & Egyed, A. (2020). Towards Optimal Assembly Line Order Sequencing with Reinforcement Learning: A Case Study. 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA).
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(Semi)automatic translation of legal regulations to formal representations: Expanding the horizon of EDA applications
Keszocze, O., Keiner, B., Richter, M., Antpöhler, G., & Wille, R. (2020). (Semi)automatic Translation of Legal Regulations to Formal Representations: Expanding the Horizon of EDA Applications. Natural Language Processing for Electronic Design Automation, 1–11.
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A scoring algorithm for abnormal passenger behavior in border-crossing areas
Vora, S., Shahriari, M., Thomopoulos, S. C. A., Fischer, L., & Hoch, T. (2020). A scoring algorithm for abnormal traveller behaviour in border crossing areas. Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies IV.
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An architecture for automated security test case generation for MQTT systems
Sochor, H., Ferrarotti, F., & Ramler, R. (2020). An Architecture for Automated Security Test Case Generation for MQTT Systems. Database and Expert Systems Applications, 48–62.
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Big Data Analytics and Knowledge Discovery. 22nd International Conference, DaWaK 2020, Bratislava, Slovakia, September 14–17, 2020, Proceeding
Song, M., Song, I.-Y., Kotsis, G., Tjoa, A. M., & Khalil, I. (Eds.). (2020). Big Data Analytics and Knowledge Discovery. Lecture Notes in Computer Science.
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Cost estimation for configurable model-driven SoC designs using machine learning
Servadei, L., Mosca, E., Devarajegowda, K., Werner, M., Ecker, W., & Wille, R. (2020). Cost Estimation for Configurable Model-Driven SoC Designs Using Machine Learning. Proceedings of the 2020 on Great Lakes Symposium on VLSI.
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Database and Expert Systems Applications DEXA 2020 International Workshops BIOKDD, IWCFS and MLKgraphs, Bratislava, Slovakia, September 14–17, 2020, Proceedings
Kotsis, G., Tjoa, A. M., Khalil, I., Fischer, L., Moser, B., Mashkoor, A., Sametinger, J., Fensel, A., & Martinez-Gil, J. (Eds.). (2020). Database and Expert Systems Applications. Communications in Computer and Information Science.
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Detecting anomalies in production quality data using a method based on The Chi-Square Test Statistic
Mayr, M., & Himmelbauer, J. (2020). Detecting Anomalies in Production Quality Data Using a Method Based on the Chi-Square Test Statistic. Lecture Notes in Computer Science, 348–363.
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Exploiting MQTT-SN for distributed reflection denial-of-service attacks
Sochor, H., Ferrarotti, F., & Ramler, R. (2020). Exploiting MQTT-SN for Distributed Reflection Denial-of-Service Attacks. Database and Expert Systems Applications, 74–81.
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Framework for data analysis in the context of the smart villages
Martinez-Gil, J., Pichler, M., Turkanović, M., Beranič, T., Gradišnik, M., Lentini, G., Lué, A., Vitale, A. C., Doukhan, G., & Belet, C. (2020). Framework for Data Analysis in the Context of the Smart Villages. Lecture Notes in Computer Science, 31–45.
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Oil and asset classes implied volatilities: Investment strategies and hedging effectiveness
Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., & de Gracia, F. P. (2020). Oil and asset classes implied volatilities: Investment strategies and hedging effectiveness. Energy Economics, 91, 104762.
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Variational optimization of informational privacy
Kumar, M., Brunner, D., Moser, B. A., & Freudenthaler, B. (2020). Variational Optimization of Informational Privacy. Database and Expert Systems Applications, 32–47.
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YASSi: Yet Another Symbolic Simulator Large (Tool Demo)
Pointner, S., Gonzalez-de-Aledo, P., & Wille, R. (2020). YASSi: Yet Another Symbolic Simulator Large (Tool Demo). Database and Expert Systems Applications, 25–31.
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A lightweight customized build chain visualization approach applied in industry
Klammer, C., & Gmeiner, J. (2020). A Lightweight Customized Build Chain Visualization Approach Applied in Industry. 2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA).
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A semi-supervised approach for network intrusion detection
Švihrová, R., & Lettner, C. (2020). A semi-supervised approach for network intrusion detection. Proceedings of the 15th International Conference on Availability, Reliability and Security.
Zur Publikation -
Advanced exact synthesis of Clifford+T Circuits
Niemann, P., Wille, R., & Drechsler, R. (2020). Advanced exact synthesis of Clifford+T circuits. Quantum Information Processing, 19(9).
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An annotated fluorescence image dataset for training nuclear segmentation methods
Kromp, F., Bozsaky, E., Rifatbegovic, F., Fischer, L., Ambros, M., Berneder, M., Weiss, T., Lazic, D., Dörr, W., Hanbury, A., Beiske, K., Ambros, P. F., Ambros, I. M., & Taschner-Mandl, S. (2020). An annotated fluorescence image dataset for training nuclear segmentation methods. Scientific Data, 7(1).
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Applying AI in practice: Key challenges and lessons learned
Fischer, L., Ehrlinger, L., Geist, V., Ramler, R., Sobieczky, F., Zellinger, W., & Moser, B. (2020). Applying AI in Practice: Key Challenges and Lessons Learned. Machine Learning and Knowledge Extraction, 451–471.
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Automated security test generation for MQTT using attack patterns
Sochor, H., Ferrarotti, F., & Ramler, R. (2020). Automated security test generation for MQTT using attack patterns. Proceedings of the 15th International Conference on Availability, Reliability and Security.
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Predicting survived and killed mutants
Duque-Torres, A., Doliashvili, N., Pfahl, D., & Ramler, R. (2020). Predicting Survived and Killed Mutants. 2020 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW).
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ToPoliNano and fiction: Design tools for field-coupled nanocomputing
Garlando, U., Walter, M., Wille, R., Riente, F., Torres, F. S., & Drechsler, R. (2020). ToPoliNano and fiction: Design Tools for Field-coupled Nanocomputing. 2020 23rd Euromicro Conference on Digital System Design (DSD).
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Bail on balancing: An alternative approach to the physical design of field-coupled nanocomputing circuits
Walter, M., Wille, R., Sill Torres, F., & Drechsler, R. (2020). Bail on Balancing: An Alternative Approach to the Physical Design of Field-Coupled Nanocomputing Circuits. 2020 IEEE Computer Society Annual Symposium on VLSI (ISVLSI).
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Differentially private learning of distributed deep models
Kumar, M., Rossbory, M., Moser, B. A., & Freudenthaler, B. (2020). Differentially Private Learning of Distributed Deep Models. Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization.
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Integrating HeuristicLab with compilers and interpreters for non-functional code optimization
Dorfmeister, D., & Krauss, O. (2020). Integrating heuristiclab with compilers and interpreters for non-functional code optimization. Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion.
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SAT-based exact physical design for field-coupled nanocomputing technologies
Walter, M., Haaswijk, W., Wille, R., Sill Torres, F., & Drechsler, R. (2020) SAT-based exact physical design for field-coupled nanocomputing technologies. IWLS 2020 - 29th International Workshop on Logic & Synthesis co-located with IEEE/ACM Design Automation Conference, San Francisco, CA, USA, July 18-19, 2020.
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A restricted second-order logic for non-deterministic poly-logarithmic time
Ferrarotti, F., GonzÁles, S., Schewe, K.-D., & Turull-Torres, J. M. (2020). A restricted second-order logic for non-deterministic poly-logarithmic time. Logic Journal of the IGPL, 28(3), 389–412.
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Detection in changes in wear-behaviour in data from continuous wear analysis
Glock, A. C. (2020) Detection in changes in wear-behaviour in data from continuous wear analysis. Master thesis, FH OÖ, Fachhochschul-Masterstudiengang Data Science and Engineering, June 2020.
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A logic for reflective ASMs
Schewe, K.-D., & Ferrarotti, F. (2020). A Logic for Reflective ASMs. Lecture Notes in Computer Science, 93–106.
Zur Publikation -
Kornia: an open source differentiable computer vision library for PyTorch
Riba, E., Mishkin, D., Ponsa, D., Rublee, E., & Bradski, G. (2020). Kornia: an Open Source Differentiable Computer Vision Library for PyTorch. 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).
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Saddle: Fast and repeatable features with good coverage
Aldana-Iuit, J., Mishkin, D., Chum, O., & Matas, J. (2020). Saddle: Fast and repeatable features with good coverage. Image and Vision Computing, 97, 3807.
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Scenario based approach in Connecting Austria for the development and validation of connect, cooperative, (semi-)automated driving in the case of intersections
Kuhn, A., Carmona, J., Schirrer, A., Hoch, T., Pollhammer, K., Hirschmann-Kraschl, K., & Schildorfer, W. (2020) Scenario based approach in Connecting Austria for the development and validation of connect, cooperative, (semi-)automated driving in the case of intersections. Proceedings of the 8th Transport Research Arena, 200-201.
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A data transformation for the estimation of decay types of multivariate distributions
Sobieczky, F., Shahriari, M., & Freudenthaler, B. (2020). A data transformation for the estimation of decay types of multivariate distributions. Procedia Manufacturing, 42, 524–527.
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A deep learning approach to the inversion of borehole resistivity measurements
Shahriari, M., Pardo, D., Picon, A., Galdran, A., Del Ser, J., & Torres-Verdín, C. (2020). A deep learning approach to the inversion of borehole resistivity measurements. Computational Geosciences, 24(3), 971–994.
Zur Publikation -
A deep neural network as surrogate model for forward simulation of borehole resistivity measurements
Shahriari, M., Pardo, D., Moser, B., & Sobieczky, F. (2020). A Deep Neural Network as Surrogate Model for Forward Simulation of Borehole Resistivity Measurements. Procedia Manufacturing, 42, 235–238.
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Adversarial robustness in data augmentation
Eghbal-zadeh, H., Koutini, K., Haunschmid, V., Primus, P., Lewandowski, M., Zellinger, W., & Widmer, G. (2020) ICLR 2020 Workshop Towards Trustworthy ML: Rethinking Security and Privacy for ML.
Zur Publikation -
An early investigation of unit testing practices of component-based software systems
Buchgeher, G., Fischer, S., Moser, M., & Pichler, J. (2020). An Early Investigation of Unit Testing Practices of Component-Based Software Systems. 2020 IEEE Workshop on Validation, Analysis and Evolution of Software Tests (VST).
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An empirical evaluation for object initialization of member variables in unit testing
Fischer, S., Haslinger, E. N., Zimmermann, M., & Thaller, H. (2020). An Empirical Evaluation for Object Initialization of Member Variables in Unit Testing. 2020 IEEE Workshop on Validation, Analysis and Evolution of Software Tests (VST).
Zur Publikation -
An integrated approach for power transformer modeling and manufacturing
Lettner, C., Moser, M., & Pichler, J. (2020). An integrated approach for power transformer modeling and manufacturing. Procedia Manufacturing, 42, 351–355.
Zur Publikation -
Enhancing industrial maintenance through intelligent data analysis
Praher, P., Freudenthaler, B., Schröder, W., & Sobieczky, F. (2020). Enhancing Industrial Maintenance Through Intelligent Data Analysis. Lecture Notes in Computer Science, 469–476.
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From pairs of most similar sequences to phylogenetic best matches
Stadler, P. F., Geiß, M., Schaller, D., López Sánchez, A., González Laffitte, M., Valdivia, D. I., Hellmuth, M., & Hernández Rosales, M. (2020). From pairs of most similar sequences to phylogenetic best matches. Algorithms for Molecular Biology, 15(1).
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General model for tracking manufacturing products using graph databases
Martinez-Gil, J., Stumptner, R., Lettner, C., Pichler, M., Mahmoud, S., Praher, P., & Freudenthaler, B. (2020). General Model for Tracking Manufacturing Products Using Graph Databases. Data-Driven Process Discovery and Analysis, 86–100.
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Leveraging machine learning for software redocumentation
Geist, V., Moser, M., Pichler, J., Beyer, S., & Pinzger, M. (2020). Leveraging Machine Learning for Software Redocumentation. 2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER).
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Live replay of screen videos: Automatically executing real applications as shown in recordings
Ramler, R., Gattringer, M., & Pichler, J. (2020). Live Replay of Screen Videos: Automatically Executing Real Applications as Shown in Recordings. 2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER).
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Predictive Maintenance - Grundvoraussetzungen, Schritte und Möglichkeiten aus Data Analytics Sicht
Freudenthaler, B. (2020) Predictive Maintenance - Grundvoraussetzungen, Schritte und Möglichkeiten aus Data Analytics Sicht. Jahrbuch Instandhaltungstage 2020, pages 131-134, April 2020.
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Proceedings of the 2020 IEEE 3rd International Workshop on Validation, Analysis, and Evolution of Software Tests (VST'20), IEEE, February 2020.
[Front cover]. (2020). 2020 IEEE Workshop on Validation, Analysis and Evolution of Software Tests (VST).
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Tackling semantic shift in industrial streaming data over time
Ehrlinger, L., Lettner, C., & Himmelbauer, J. (2020) Tackling semantic shift in industrial streaming data over time Proceedings of the 12th International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2020), pages 36-39, IARIA, October 2020.
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Towards fault localization via probabilistic software modeling
Thaller, H., Linsbauer, L., Egyed, A., & Fischer, S. (2020). Towards Fault Localization via Probabilistic Software Modeling. 2020 IEEE Workshop on Validation, Analysis and Evolution of Software Tests (VST).
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Unimodularity of network representations of time-series for unbiased parameter estimation
Sobieczky, F. (2020). Unimodularity of Network Representations of Time-Series for Unbiased Parameter Estimation. Lecture Notes in Computer Science, 167–175.
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Addressing evolving requirements faced by the software industry
Biró, M., Colomo‐Palacios, R., & Messnarz, R. (2020). Addressing evolving requirements faced by the software industry. Journal of Software: Evolution and Process, 32(3). Portico.
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Borehole resistivity simulations of oil-water transition zones with a 1.5D numerical solver
Shahriari, M., & Pardo, D. (2020). Borehole resistivity simulations of oil-water transition zones with a 1.5D numerical solver. Computational Geosciences, 24(3), 1285–1299.
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Special Issue: Addressing Evolving Requirements Faced by the Software Industry
Issue Information. (2020). Journal of Software: Evolution and Process, 32(3). Portico.
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To index or not to index: Time–space trade-offs for positional ranking functions in search engines
Arroyuelo, D., González, S., Marin, M., Oyarzún, M., Suel, T., & Valenzuela, L. (2020). To index or not to index: Time–space trade-offs for positional ranking functions in search engines. Information Systems, 89, 101466.
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A framework for factory-trained virtual sensor models based on censored production data
Luftensteiner, S., & Zwick, M. (2020). A Framework for Factory-Trained Virtual Sensor Models Based on Censored Production Data. Database and Expert Systems Applications, 3–16.
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An optimal (∊,δ)-differentially private learning of distributed deep fuzzy model
Kumar, M., Rossbory, M., Moser, B. A., & Freudenthaler, B. (2021). An optimal (∊,δ)-differentially private learning of distributed deep fuzzy models. Information Sciences, 546, 87–120.
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Automated test reuse for highly configurable software
Fischer, S., Michelon, G. K., Ramler, R., Linsbauer, L., & Egyed, A. (2020). Automated test reuse for highly configurable software. Empirical Software Engineering, 25(6), 5295–5332.
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Domain-invariant regression under Beer-Lambert’s Law
Nikzad-Langerodi, R., Zellinger, W., Saminger-Platz, S., & Moser, B. (2019). Domain-Invariant Regression Under Beer-Lambert’s Law. 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA).
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Moment-based domain adaption: Learning bounds and algorithms
PhD thesis, Joahnnes Kepler University Linz, Doctoral Program Technische Wissenschaften, February 2020.
Zur Publikation -
Software Competence Center Hagenberg: Wissens- und Technologietransfer in Software und Data Science
In M. Felderer, W. Hasselbring, R. Rabiser, R. Jung (Hrsg), Software Engineering 2020, Fachtagung des GI-Fachbereichs Softwaretechnik, Lecture Notes in Informatics - Proceedings Series of the Gesellschaft für Informatik (GI), volume P-300, pages 225-227, DOI 10.18420/SE2020_61, Gesellschaft für Informatik e.V., February 2020.
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Software Engineering: Forschung - Innovation - Transfer
Sauer, Stefan, & Ramler, Rudolf. (2020). Software Engineering: Forschung - Innovation - Transfer.
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The SERUMS tool-chain: Ensuring security and privacy of medical data in smart patient-centric healthcare systems
Janjic, V., Bowles, J. K. F., Vermeulen, A. F., Silvina, A., Belk, M., Fidas, C., Pitsillides, A., Kumar, M., Rossbory, M., Vinov, M., Given-Wilson, T., Legay, A., Blackledge, E., Arredouani, R., Stylianou, G., & Huang, W. (2019). The SERUMS tool-chain: Ensuring Security and Privacy of Medical Data in Smart Patient-Centric Healthcare Systems. 2019 IEEE International Conference on Big Data (Big Data).
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Vers une évolution cohérente des systémes dynamiques á partir des méthodes formelles
PhD thesis, Université Abdelhamid Ibn Badis Mostaganem, February 2020.
Zur Publikation -
Formalizing architectural rules with ontologies - An industrial evaluation
Schroder, S., & Buchgeher, G. (2019). Formalizing Architectural Rules with Ontologies - An Industrial Evaluation. 2019 26th Asia-Pacific Software Engineering Conference (APSEC).
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Mixture density generative adversarial networks
Eghbal-zadeh, H., Zellinger, W., & Widmer, G. (2019). Mixture Density Generative Adversarial Networks. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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Proper hierarchies in polylogarithmic time and absence of complete problems
Ferrarotti, F., González, S., Schewe, K.-D., & Turull-Torres, J. M. (2020). Proper Hierarchies in Polylogarithmic Time and Absence of Complete Problems. Foundations of Information and Knowledge Systems, 90–105.
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A systematic mapping study on best practices for domain-specific modeling
Czech, G., Moser, M., & Pichler, J. (2019). A systematic mapping study on best practices for domain-specific modeling. Software Quality Journal, 28(2), 663–692.
Zur Publikation -
Analyse-Tools zur Verwendung bei Gelelektorphorese
Mayer, R. (2020) Analyse-Tools zur Verwendung bei Gelelektorphorese. Bachelor thesis, FH OÖ, Fachhochschul-Bachelorstudiengang Medizin- und Bioinformatik, May 2020.
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Feature Extraction for Day-ahead Electricity-Load Forecasting in Residential Buildings
Kychkin, A. V., & Chasparis, G. C. (2020). Feature Extraction for Day-ahead Electricity-Load Forecasting in Residential Buildings. IFAC-PapersOnLine, 53(2), 13094–13100.
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Reinforcement-Learning-based Optimization for Day-ahead Flexibility Extraction in Battery Pools
Chasparis, G. C., & Lettner, C. (2020). Reinforcement-Learning-based Optimization for Day-ahead Flexibility Extraction in Battery Pools. IFAC-PapersOnLine, 53(2), 13351–13358.
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ReLU code space: A basis for rating network quality besides accuracy
Shepeleva, Natalia, Zellinger, Werner, Lewandowski, Michal, & Moser, Bernhard. (2020). ReLU Code Space: A Basis for Rating Network Quality Besides Accuracy (Version 1). arXiv.
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Transformation of java source code to base-level Abstract State Machine. Design and implementation
Ferrarotti, F., Moser, M., & Pichler, J. (2020) Transformation of java source code to base-level Abstract State Machine. Design and implementation. Technical Report, number SCCH-TR-20058, Software Competence Center Hagenberg, July 2020.
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2019
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Formal design of scalable conversation protocols using Event‐B: Validation, experiments, and benchmark
Benyagoub, S., Aït‐Ameur, Y., Ouederni, M., Mashkoor, A., & Medeghri, A. (2019). Formal design of scalable conversation protocols using Event‐B: Validation, experiments, and benchmarks. Journal of Software: Evolution and Process, 32(2). Portico.
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Optimal selection of training courses for unemployed people based on stable marriage model
Martinez-Gil, J., & Freudenthaler, B. (2019). Optimal Selection of Training Courses for Unemployed People based on Stable Marriage Model. Proceedings of the 21st International Conference on Information Integration and Web-Based Applications & Services.
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Special Issue: Security- and safety-critical cyber-physical systems
Mashkoor, A., Sametinger, J., Biro, M., & Egyed, A. (2019). Security‐ and safety‐critical cyber‐physical systems. Journal of Software: Evolution and Process, 32(2). Portico.
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Special Issue: Security‐ and Safety‐Critical Cyber‐Physical Systems
Mashkoor, A., Sametinger, J., Biro, M., & Egyed, A. (2019). Security‐ and safety‐critical cyber‐physical systems. Journal of Software: Evolution and Process, 32(2). Portico.
Zur Publikation -
Design and validation of a C++ code generator from Abstract State Machines specifications
Bonfanti, S., Gargantini, A., & Mashkoor, A. (2019). Design and validation of a C++ code generator from Abstract State Machines specifications. Journal of Software: Evolution and Process, 32(2). Portico.
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Detection of anomalous events in the wear-behaviour of continuously recorded sliding friction pairs
Glock, A.-C., Sobieczky, F., & Jech, M. (2019). Detection of anomalous events in the wear-behaviour of continuously recorded sliding friction pairs. Symposium 2019 Tribologie in Industrie und Forschung, pages 33-40, ÖTG, November 2019.
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Establishing a user-centered design process for human-machine interfaces: Threats to success
Winterer, M., Salomon, C., Buchgeher, G., Zehethofer, M., & Derntl, A. (2019). Establishing a User-Centered Design Process for Human-Machine Interfaces: Threats to Success. Lecture Notes in Computer Science, 89–102.
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Facing mental workload in AI-transformed working environments
Gusenleitner, N., Siedl, S., Stübl, G., Polleres, A., Recski, G., Sommer, R., Leva, M. C., Pichler, M., Kopetzky, T., &Moser, B. (2019). Facing mental workload in AI-transformed working environments. H-WORKLOAD 2019 : 3rd International Symposium on Human Mental Workload: Models and Applications, Rome, Italy, November 14-15, 2019.
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Improving quality of data exchange files. An industrial case study
Fleck, G., Moser, M., & Pichler, J. (2019). Improving Quality of Data Exchange Files. An Industrial Case Study. Lecture Notes in Computer Science, 161–175.
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Integrating threat modeling and automated test case generation into industrialized software security testing
Marksteiner, S., Ramler, R., & Sochor, H. (2019). Integrating Threat Modeling and Automated Test Case Generation into Industrialized Software Security Testing. Proceedings of the Third Central European Cybersecurity Conference.
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Multifaceted consistency checking of collaborative engineering artifacts
Trols, M. A., Mashkoor, A., & Egyed, A. (2019). Multifaceted Consistency Checking of Collaborative Engineering Artifacts. 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C).
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New Trends in Model and Data Engineering, MEDI 2019 International Workshops, DETECT, DSSGA, TRIDENT, Toulouse, France, October 28–31, 2019, Proceedings, Communications in Computer and Information Science, volume 1085
Attiogbé, C., Ferrarotti, F., & Maabout, S. (Eds.). (2019). New Trends in Model and Data Engineering. Communications in Computer and Information Science.
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Predictive Maintenance - Projektbeispiele aus der anwendungsorientierten Forschung
Freudenthaler, B. (2019). Predictive Maintenance - Projektbeispiele aus der anwendungsorientierten Forschung. Symposium 2019 Tribologie in Industrie und Forschung, pages 5-10, ÖTG, November 2019.
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A general framework for multiple choice question answering based on mutual information and reinforced co-occurrence
Martinez-Gil, J., Freudenthaler, B., & Tjoa, A. M. (2019). A General Framework for Multiple Choice Question Answering Based on Mutual Information and Reinforced Co-occurrence. Lecture Notes in Computer Science, 91–110.
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Automatic design of semantic similarity controllers based on fuzzy logics
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2019). Automatic design of semantic similarity controllers based on fuzzy logics. Expert Systems with Applications, 131, 45–59.
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BSP abstract state machines capture bulk synchronous prallel computations
Ferrarotti, F., González, S., & Schewe, K.-D. (2019). BSP abstract state machines capture bulk synchronous parallel computations. Science of Computer Programming, 184, 102319.
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Enhancing acceptance test-driven development with model-based test generation
Ramler, R., & Klammer, C. (2019). Enhancing Acceptance Test-Driven Development with Model-Based Test Generation. 2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C).
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Extracting high-level system specifications from source code via abstract state machines
Ferrarotti, F., Pichler, J., Moser, M., & Buchgeher, G. (2019). Extracting High-Level System Specifications from Source Code via Abstract State Machines. Lecture Notes in Computer Science, 267–283.
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Facilitating the digital transformation of villages
Beranič, T., Zamuda, A., Brezočnik, L., Lentini, G., Polettini, F., Lue, A., Colorni Vitale, A., Martinez-Gil, J., Pichler, M., & Turkanović, M. (2019) Facilitating the digital transformation of villages. Proceedings of the Central European Conference on Information and Intelligent Systems (CECIIS 2019), pages 281-288, October 2019.
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Fuzzy membership functional analysis for nonparametric deep models of image features
Kumar, M., & Freudenthaler, B. (2020). Fuzzy Membership Functional Analysis for Nonparametric Deep Models of Image Features. IEEE Transactions on Fuzzy Systems, 28(12), 3345–3359.
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Multi-source transfer learning of time series in cyclical manufacturing
Zellinger, W., Grubinger, T., Zwick, M., Lughofer, E., Schöner, H., Natschläger, T., & Saminger-Platz, S. (2019). Multi-source transfer learning of time series in cyclical manufacturing. Journal of Intelligent Manufacturing, 31(3), 777–787.
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Robust generalized fuzzy systems training from high-dimensional time-series data using local structure preserving PLS
Lughofer, E., & Nikzad-Langerodi, R. (2020). Robust Generalized Fuzzy Systems Training From High-Dimensional Time-Series Data Using Local Structure Preserving PLS. IEEE Transactions on Fuzzy Systems, 28(11), 2930–2943.
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A cooperative demand-response framework for day-ahead optimization in battery pools
Chasparis, G. C., Pichler, M., Spreitzhofer, J., & Esterl, T. (2019). A cooperative demand-response framework for day-ahead optimization in battery pools. Energy Informatics, 2(S1).
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A deep learning model for detecting sarcasm in written product reviews
Schwarz, N. (2019) A deep learning model for detecting sarcasm in written product reviews. Master thesis, FH OÖ, Fachhochschul-Masterstudiengang Data Science and Engineering, September 2019.
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A framework for unsupervised anomaly detection in production quality data
Mayr, M. (2019). A framework for unsupervised anomaly detection in production quality data. Master thesis, FH OÖ, Fachhochschul-Masterstudiengang Data Science and Engineering, September 2019.
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A recommender system for software architecture decision making
Brandner, K., & Weinreich, R. (2019). A recommender system for software architecture decision making. Proceedings of the 13th European Conference on Software Architecture - Volume 2.
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An event-driven approach for time-domain recognition of spoken english letters
Qaisar, S. M., Laskar, S., Lunglmayr, M., Moser, B. A., Abdulbaqi, R., & Banafia, R. (2019). An Event-Driven Approach for Time-Domain Recognition of Spoken English Letters. 2019 5th International Conference on Event-Based Control, Communication, and Signal Processing (EBCCSP).
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Applicability of controlled natural languages for architecture analysis and documentation: an industrial case study
Schröder, S., & Buchgeher, G. (2019). Applicability of controlled natural languages for architecture analysis and documentation. Proceedings of the 13th European Conference on Software Architecture - Volume 2.
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Automating test reuse for highly configurable software
Fischer, S., Ramler, R., Linsbauer, L., & Egyed, A. (2019). Automating Test Reuse for Highly Configurable Software. Proceedings of the 23rd International Systems and Software Product Line Conference - Volume A.
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Design and implementation of a graph-based solution for tracking manufacturing products
Martinez-Gil, J., Stumpner, R., Lettner, C., Pichler, M., & Fragner, W. (2019). Design and Implementation of a Graph-Based Solution for Tracking Manufacturing Products. New Trends in Databases and Information Systems, 417–423.
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Discovering architectural rules in practice
Schröder, S., & Buchgeher, G. (2019). Discovering architectural rules in practice. Proceedings of the 13th European Conference on Software Architecture - Volume 2.
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Framework for assessing the smartness maturity level of villages
Martinez-Gil, J., Pichler, M., Beranič, T., Brezočnik, L., Turkanović, M., Lentini, G., Polettini, F., Lué, A., Vitale, A. C., Doukhan, G., & Belet, C. (2019). Framework for Assessing the Smartness Maturity Level of Villages. New Trends in Databases and Information Systems, 501–512.
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Neue Programmiersprachen im Web
Piereder, C. (2019). Neue Programmiersprachen im Web. Bachelor thesis, FH OÖ, Fachhochschul-Bachelorstudiengang Software Engineering, September 2019.
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Tradeoff analysis of discrepancy-based adaptive thresholding approach
Lunglmayr, M., Qaisar, S. M., & Moser, B. A. (2019). Tradeoff Analysis of Discrepancy-Based Adaptive Thresholding Approach. 2019 5th International Conference on Event-Based Control, Communication, and Signal Processing (EBCCSP).
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A DaQL to monitor data quality in machine learning applications
Ehrlinger, L., Haunschmid, V., Palazzini, D., & Lettner, C. (2019). A DaQL to Monitor Data Quality in Machine Learning Applications. Database and Expert Systems Applications, 227–237.
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An efficient design for a multi-objective evolutionary algorithm to generate DNA libraries suitable for computation
Chaves-González, J. M., & Martínez-Gil, J. (2018). An Efficient Design for a Multi-objective Evolutionary Algorithm to Generate DNA Libraries Suitable for Computation. Interdisciplinary Sciences: Computational Life Sciences, 11(3), 542–558.
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Deriving an optimal noise adding mechanism for privacy-preserving machine learning.
Kumar, M., Rossbory, M., Moser, B. A., & Freudenthaler, B. (2019). Deriving an Optimal Noise Adding Mechanism for Privacy-Preserving Machine Learning. Database and Expert Systems Applications, 108–118.
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Lessons learned from making the transition to model-based GUI testing
Ramler, R., Klammer, C., & Wetzlmaier, T. (2019). Lessons learned from making the transition to model-based GUI testing. Proceedings of the 10th ACM SIGSOFT International Workshop on Automating TEST Case Design, Selection, and Evaluation.
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Measurement-based efficient resource allocation with demand-side adjustments
Chasparis, G. C. (2019). Measurement-based efficient resource allocation with demand-side adjustments. Automatica, 106, 274–283.
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ML-PipeDebugger: A debugging tool for data processing pipelines?
Kossak, F., & Zwick, M. (2019). ML-PipeDebugger: A Debugging Tool for Data Processing Pipelines. Database and Expert Systems Applications, 263–272.
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Multiple choice question answering in the legal domain using reinforced co-occurrence
Martinez-Gil, J., Freudenthaler, B., & Tjoa, A. M. (2019). Multiple Choice Question Answering in the Legal Domain Using Reinforced Co-occurrence. Database and Expert Systems Applications, 138–148.
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On conditioning GANs to hierarchical ontologies
Eghbal-zadeh, H., Fischer, L., & Hoch, T. (2019). On Conditioning GANs to Hierarchical Ontologies. Database and Expert Systems Applications, 182–186.
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Security risk mitigation of cyber physical systems: A case study of a flight simulator
Zahid, M., Inayat, I., Mashkoor, A., & Mehmood, Z. (2019). Security Risk Mitigation of Cyber Physical Systems: A Case Study of a Flight Simulator. Database and Expert Systems Applications, 129–138.
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Shifting paradigms in innovation management – Organic growth strategies in the cloud
Messnarz, R., Sauberer, G., Mac an Airchinnigh, M., Biro, M., Ekert, D., & Reiner, M. (2019). Shifting Paradigms in Innovation Management – Organic Growth Strategies in the Cloud. Systems, Software and Services Process Improvement, 28–42.
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Improving offline deep learning models by censored online data and quadratic programming
Luftensteiner, S. (2019) Improving offline deep learning models by censored online data and quadratic programming. Master thesis, FH OÖ, Fachhochschul-Masterstudiengang Software Engineering, July 2019.
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The polylog-time hierarchy captured by restricted second-order logic
Ferrarotti, F., Gonzalez, S., Schewe, K.-D., & Turull-Torres, J. M. (2018). The Polylog-Time Hierarchy Captured by Restricted Second-Order Logic. 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC).
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Towards a data-driven approach for fraud detection in the social insurance field: A case study in Upper Austria
Himmelbauer, J., Martinez-Gil, J., Ksen, M., Linner, K., & Plakolm, S. (2019). Towards a Data-Driven Approach for Fraud Detection in the Social Insurance Field: A Case Study in Upper Austria. Lecture Notes in Computer Science, 70–84.
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A demand-response framework in balance groups through direct battery-storage control
Chasparis, G. C., Pichler, M., & Natschlager, T. (2019). A Demand-Response Framework in Balance Groups through Direct Battery-Storage Control. 2019 18th European Control Conference (ECC).
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A novel approach for learning how to automatically match job offers and candidate profiles
Martinez-Gil, J., Paoletti, A. L., & Pichler, M. (2019). A Novel Approach for Learning How to Automatically Match Job Offers and Candidate Profiles. Information Systems Frontiers, 22(6), 1265–1274.
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Collaboratively enhanced consistency checking in a cloud-based engineering environment
Tröls, M. A., Mashkoor, A., & Egyed, A. (2019). Collaboratively enhanced consistency checking in a cloud-based engineering environment. Proceedings of the ACM SIGCHI Symposium on Engineering Interactive Computing Systems.
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Descriptive complexity of deterministic polylogarithmic time
Ferrarotti, F., González, S., Turull Torres, J. M., Van den Bussche, J., & Virtema, J. (2019). Descriptive Complexity of Deterministic Polylogarithmic Time. Lecture Notes in Computer Science, 208–222.
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Optimization heuristics for computing the voronoi skeleton
Kotsur, D., & Tereshchenko, V. (2019). Optimization Heuristics for Computing the Voronoi Skeleton. Computational Science – ICCS 2019, 96–111.
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Architecture-aware design and implementation of CNN algorithms for embedded inference: The ALOHA project
Meloni, P., Loi, D., Deriu, G., Pimentel, A. D., Saprat, D., Pintort, M., Biggio, B., Ripolles, O., Solans, D., Conti, F., Benini, L., Stefanov, T., Minakova, S., Moser, B., Shepeleva, N., Masin, M., Palumbo, F., Fragoulis, N., & Theodorakopoulos, I. (2018). Architecture-aware design and implementation of CNN algorithms for embedded inference: the ALOHA project. 2018 30th International Conference on Microelectronics (ICM).
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On quasi-isometry of threshold-based sampling
Moser, B. A., & Lunglmayr, M. (2019). On Quasi-Isometry of Threshold-Based Sampling. IEEE Transactions on Signal Processing, 67(14), 3832–3841.
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Robust unsupervised domain adaptation for neural networks via moment alignment
Zellinger, W., Moser, B. A., Grubinger, T., Lughofer, E., Natschläger, T., & Saminger-Platz, S. (2019). Robust unsupervised domain adaptation for neural networks via moment alignment. Information Sciences, 483, 174–191.
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Semantic similarity aggregators for very short textual expressions: A case study on landmarks and points of interest
Martinez-Gil, J. (2019). Semantic similarity aggregators for very short textual expressions: a case study on landmarks and points of interest. Journal of Intelligent Information Systems, 53(2), 361–380.
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Thirteen years of SysML: A systematic mapping study
Wolny, S., Mazak, A., Carpella, C., Geist, V., & Wimmer, M. (2019). Thirteen years of SysML: a systematic mapping study. Software and Systems Modeling, 19(1), 111–169.
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Using decision models for documenting microservice architectures: A student experiment and focus group study
Haselbock, S., Weinreich, R., & Buchgeher, G. (2019). Using Decision Models for Documenting Microservice Architectures: A Student Experiment and Focus Group Study. 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE).
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A novel data quality metric for minimality
Ehrlinger, L., & Wöß, W. (2019). A Novel Data Quality Metric for Minimality. Data Quality and Trust in Big Data, 1–15.
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Automated schema quality measurement in large-scale information systems
Ehrlinger, L., & Wöß, W. (2019). Automated Schema Quality Measurement in Large-Scale Information Systems. Data Quality and Trust in Big Data, 16–31.
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Fuzzy theoretic model based analysis of image features
Kumar, M., Chatterjee, S., Zhang, W., Yang, J., & Kolbe, L. M. (2019). Fuzzy theoretic model based analysis of image features. Information Sciences, 480, 34–54.
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Live and global consistency checking in a collaborative engineering environment
Tröls, M. A., Mashkoor, A., & Egyed, A. (2019). Live and global consistency checking in a collaborative engineering environment. Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing.
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An algorithm for individual intermediate filament tracking
Kotsur, D., Yakobenchuk, R., Leube, R. E., Windoffer, R., & Mattes, J. (2019). An Algorithm for Individual Intermediate Filament Tracking. Lecture Notes in Computer Science, 66–74.
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Feature Maps: A Comprehensible Software Representation for Design Pattern Detection
Thaller, H., Linsbauer, L., & Egyed, A. (2019). Feature Maps: A Comprehensible Software Representation for Design Pattern Detection. 2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER).
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Learning-based dynamic pinning of parallelized applications in many-core systems
Chasparis, G. C., Rossbory, M., Janjic, V., & Hammond, K. (2019). Learning-Based Dynamic Pinning of Parallelized Applications in Many-Core Systems. 2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP).
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Leveraging outdoor webcams for local descriptor learning
Pultar, Milan, Mishkin, Dmytro, & Matas, Jiri. (2019). Leveraging Outdoor Webcams for Local Descriptor Learning. Verlag der Technischen Universität Graz.
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An expert interview study on areas of microservice design
Haselbock, S., Weinreich, R., & Buchgeher, G. (2018). An Expert Interview Study on Areas of Microservice Design. 2018 IEEE 11th Conference on Service-Oriented Computing and Applications (SOCA).
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Benefits and drawbacks of representing and analyzing source code and software engineering artifacts with graph databases
Ramler, R., Buchgeher, G., Klammer, C., Pfeiffer, M., Salomon, C., Thaller, H., & Linsbauer, L. (2018). Benefits and Drawbacks of Representing and Analyzing Source Code and Software Engineering Artifacts with Graph Databases. Software Quality: The Complexity and Challenges of Software Engineering and Software Quality in the Cloud, 125–148.
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Decentralized energy networks based on blockchain: Background, overview and concept discussion
Pichler, M., Meisel, M., Goranovic, A., Leonhartsberger, K., Lettner, G., Chasparis, G., Vallant, H., Marksteiner, S., & Bieser, H. (2019). Decentralized Energy Networks Based on Blockchain: Background, Overview and Concept Discussion. Lecture Notes in Business Information Processing, 244–257.
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Microservice design space analysis and decision documentation: A case study on API management
Haselbock, S., Weinreich, R., Buchgeher, G., & Kriechbaum, T. (2018). Microservice Design Space Analysis and Decision Documentation: A Case Study on API Management. 2018 IEEE 11th Conference on Service-Oriented Computing and Applications (SOCA).
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Stochastic Stability of Perturbed Learning Automata in Positive-Utility Games
Chasparis, G. C. (2019). Stochastic Stability of Perturbed Learning Automata in Positive-Utility Games. IEEE Transactions on Automatic Control, 64(11), 4454–4469.
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Why software testing fails: Common pitfalls observed in a critical smart metering project
Mohacsi, S., & Ramler, R. (2018). Why Software Testing Fails: Common Pitfalls Observed in a Critical Smart Metering Project. Software Quality: The Complexity and Challenges of Software Engineering and Software Quality in the Cloud, 73–92.
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A schema readability metric for automated data quality measurement
Ehrlinger, L., Huszar, G., & Wöß, W. (2019). A schema readability metric for automated data quality measurement. Proceedings of the 11th International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2019), pages 4-10, IARIA, June 2019.
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Enhancing industrial maintenance through intelligent data analysis
Praher, P., Freudenthaler, B., Schröder, W., & Sobieczky, F. (2020). Enhancing Industrial Maintenance Through Intelligent Data Analysis. Lecture Notes in Computer Science, 469–476.
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Towards a knowledge graph to describe and process data defects
Borovina Josko, J. M., Ehrlinger, L., & Wöß, W. (2019). Towards a knowledge graph to describe and process data defects. Proceedings of the 11th International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2019), pages 57-60, IARIA, June 2019.
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Unimodularity of network representations of time-series for unbiased parameter estimation
Sobieczky, F. (2020). Unimodularity of Network Representations of Time-Series for Unbiased Parameter Estimation. Lecture Notes in Computer Science, 167–175.
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2018
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Multi-parameter online measurement IoT system based on BP neural network algorithm
Zhang, W., Kumar, M., & Liu, J. (2018). Multi-parameter online measurement IoT system based on BP neural network algorithm. Neural Computing and Applications, 31(12), 8147–8155.
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An adaptive fuzzy filter for image denoising
Zhang, W., Kumar, M., Yang, J., Zhou, Y., & Mao, Y. (2018). An adaptive fuzzy filter for image denoising. Cluster Computing, 22(S6), 14107–14124.
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