| 2010 |
| 0916 | R. Ramler, T. Natschläger. Building defect prediction models in practice. Technical Report, SCCH-TR-0916, 2010. |
| 2009 |
| 0909 | W. Beer, W. Kurschl, F. Matusek, S. Mitsch, B. Moser, T. Natschläger, J. Schönböck, S. Sutor. Application development and management of smart camera networks.
In Ahmed Nabil Belbachir (editor).
Smart Cameras, pages 259-266, Springer Berlin Heidelberg. 2009. |
| 0940 | G. Guta, B. Moser, T. Natschläger. Machine learning extended by semantic reasoning for knowledge discovery of sensory data. Technical Report, SCCH-TR-0940, 2009. |
| 0914 | D. Pecevski, T. Natschläger, K. Schuch. PCSIM: A parallel simulation environment for neural. Frontiers in Neuroinformatics, volume 3, number 11, pages doi:10.3389/neuro.11/011.2009, 2009. |
| 0917 | R. Ramler, S. Larndorfer, T. Natschläger. What software repositories should be mined for defect predictors?. Proceedings oft the 35th Euromicro Conference on Software Engineering and Advanced Applications (SEAA 2009), pages 181-187, IEEE Computer Society. 2009. |
| 0915 | R. Ramler, K. Wolfmaier, E. Stauder, F. Kossak, T. Natschläger. Key questions in building defect prediction models in practice.
In F. Bomarius, M. Oivo, P. Jaring, P. Abrahamsson (editors).
Key Questions in Building Defect Prediction Models in Practice - Proceedings 10th International Confercne PROFES 2009, Lecture Notes in Business Information Processing, pages 14-27, Springer Berlin Heidelberg. 2009. |
| 2008 |
| 0816 | W. Beer, J. Pichler, T. Natschläger, B. Moser. Integratives wissensbasiertes Modell Lebenszyklus-Management von Kalkulations- und Prozessmodellen: eine Vision. Tagungsband Industrielles Symposium Mechatronik Automatisierung, pages 241-245, Clusterland Oberösterreich GmbH / Mechatronik-Cluster. 2008. |
| 0819 | T. Natschläger, J. Himmelbauer, H. Schöner, F. Kokert, S. Mitter, H. Exner. Wissensextraktion mittels maschinellen Lernens zum besseren Prozessverständnis in der Stahlerzeugung. Tagungsband Industrielles Symposium Mechatronik Automatisierung, pages 79-87, Clusterland Oberösterreich GmbH / Mechatronik-Cluster. 2008. |
| 0818 | T. Natschläger, W. Traunmüller, K. Reingruber, H. Exner. Lokal optimierte Wetterprognosen zur Regelung stark umweltbeeinflusster Systeme. Tagungsband Industrielles Symposium Mechatronik Automatisierung, pages 281-284, Clusterland Oberösterreich GmbH / Mechatronik-Cluster. 2008. |
| 2007 |
| 0637 | R. Brette, M. Zirpe, T. Natschläger, D. Pecevski, B. Ermentrout, M. Djurfeldt, A. Lasner, O. Rochel, T. Vieville, E. Muller, A. Davison, M. Rudolph, S. El Boustani, A. Destexhe, T. Cernevale, M. Hines, D. Beeman, J. Bower, M. Diemann, P. Goodman, F. Harris, Jr.. Simulation ot network of spiking neuros: A review of tools and strategies. Journal fof Cumputational Neuroscience, volume 23, number 3, pages 349-398, 2007. |
| 0707 | R. Ramler, K. Wolfmaier, T. Natschläger. Observing distributions in size metrics: Experience from analyzing large software systems. Proc. 31st IEEE Int. Computer Software and Applications Conference, pages 299-304, IEEE Computer Society. 2007. |
| 2005 |
| 0420 | T. Natschläger, N. Bertschinger, R. Lengstein. At the edge of chaos: Real-time computations and self-organized criticality in recurrent neural networks.
In L.K. Saul, Y. Weiss, L. Bottou (editors).
Proc. of NIPS 2004, Advances in Neural Information Processing Systems, pages 145-152, MIT Press. 2005. |
| 0531 | T. Natschläger, M. Drobics, F. Kossak. machine learning framework for Mathematica V1.3: Creating interpretable computational models from data. Proc. Wolfram Technology Conf., pages online, 2005. |
| 0419 | T. Natschläger, W. Maass. Dynamics of information and emergent computation in generic microcircuit models. Neural Networks, volume 18, number 10, pages 1301-1308, 2005. |
| 2004 |
| 0324 | N. Bertschinger, T. Natschläger. Real-time computation at the edge of chaos in recurrent neural networks. Neural Computation, volume 16, number 7, pages 1413-1436, 2004. |
| 0425 | M. Drobics, F. Kossak, T. Natschläger. machine learning framework for Mathematica V1.2 - Creating interpretable computational models from data. Proc. Mathematica Technology Conf., pages online, 2004. |
| 0430 | T. Natschläger, N. Bertschinger. Supplementary information to the mean-field theory for randomly connected recurrent network of threshold gates. Technical Report, SCCH-TR-0430, SCCH, 2004. |
| 0403 | T. Natschläger, F. Kossak, M. Drobics. Extracting knowledge and computable models from data - Needs, expectations, and experience. Proc. 13th IEEE Int. Conf. on Fuzzy Systems, pages 493 - 498, IEEE Press. 2004. |