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Order by: Author  Year  Journal

2013

Dynamic state estimation based on Poisson spike trains—towards a theory of optimal encoding

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

Journal of Statistical Mechanics: Theory and Experiment, P03009. 2013

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2012

Bayesian Inference for Change Points in Dynamical Systems with Reusable States—a Chinese Restaurant Process Approach

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

Proceedings of the International Conference on Artificial Intelligence and Statistics 2012

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Optimal control as a graphical model inference problem

Kappen, H. J., Gomez, V. and Opper, M.

Machine Learning. Springer, 159-182. 2012

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2011

Balancing a pole

Sobierajski, K. and Sikora, P.

2011

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

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

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Inference in continuous-time change-point models

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

Advances in Neural Information Processing Systems 24, 2717–2725. 2011

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