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Gaussian Processes for Global Optimization [21]

Hjelm, M. and Han, J.-W.

2011

Link zur Publikation [22] Download Bibtex Eintrag [23]

Eine neue Methode zur Lösung eindimensionaler Modelle mit Unordnung (A new method for solving one dimensional models with disorder) [24]

Opper, M.

1987 Giessen University, Germany

Download Bibtex Eintrag [25]

Optimal Neural Codes for Control and Estimation [26]

Susemihl, A. K., Meir, R. and Opper, M.

Advances in Neural Information Processing Systems 27. Curran Associates, Inc., 2987–2995. 2014

Link zur Publikation [27] Download Bibtex Eintrag [28]

Balancing a pole [29]

Sobierajski, K. and Sikora, P.

2011

Link zur Publikation [30] Download Bibtex Eintrag [31]

Synchronization of neural networks by mutual learning and its application to cryptography [32]

Klein, E., Mislovaty, R., Kanter, I., Ruttor, A. and Kinzel, W.

Advances in Neural Information Processing Systems. MIT Press, 689-696. 2005

Link zur Publikation [33] Download Bibtex Eintrag [34]

Inference Approaches to Optimal Control [35]

Lu, J., Peng, L., Liu, S. and Liu, Y.

2011

Link zur Publikation [36] Download Bibtex Eintrag [37]

Learning to Ride a Light Cycle [38]

Haenicke, J.

2011

Link zur Publikation [39] Download Bibtex Eintrag [40]

Schlüsselaustausch mit neuronalen Netzen [41]

Ruttor, A.

2003 Universität Würzburg

Link zur Publikation [42] Download Bibtex Eintrag [43]

Neural Synchronization and Cryptography [44]

Ruttor, A.

2007 University of Wuerzburg

Link zur Publikation [45] Download Bibtex Eintrag [46]

Approximate inference for stochastic reaction processes [47]

Ruttor, A., Sanguinetti, G. and Opper, M.

Learning and Inference in Computational Systems Biology. MIT Press, 189-205. 2010

Link zur Publikation [48] Download Bibtex Eintrag [49]

Approximate parameter inference in a stochastic reaction-diffusion model [50]

Ruttor, A. and Opper, M.

Proceedings of The Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS) 2010. JMLR, 669-676. 2010

Link zur Publikation [51] Download Bibtex Eintrag [52]

Approximate inference in continuous time Gaussian-Jump processes [53]

Opper, M., Ruttor, A. and Sanguinetti, G.

Advances in Neural Information Processing Systems 23, 1831–1839. 2010

Link zur Publikation [54] Download Bibtex Eintrag [55]

Comparing diffusion and weak noise approximations for inference in reaction models [56]

Ruttor, A., Stimberg, F. and Opper, M.

Proceedings of the Fourth International Workshop on Machine Learning in Systems Biology (October 15-16, 2010, Edinburgh, UK), 149–152. 2010

Link zur Publikation [57] Download Bibtex Eintrag [58]

MCMC for continuous time switching models [59]

Stimberg, F., Ruttor, A. and Opper, M.

NIPS Workshop on Monte Carlo Methods for Modern Applications (December 10, 2010, Whistler, Canada) 2010

Link zur Publikation [60] Download Bibtex Eintrag [61]

Bayesian Inference for Models of Transcriptional Regulation Using Markov Chain Monte Carlo Sampling [62]

Stimberg, F., Ruttor, A. and Opper, M.

Proceedings of the 8th International Workshop on Computational Systems Biology (WCSB). Tampere University of Technology, Tampere, Finland, 169–172. 2011

Link zur Publikation [63] Download Bibtex Eintrag [64]
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