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TU Berlin

Inhalt des Dokuments

Prof. Dr. Manfred Opper

Lupe
  • Leiter der Einheit KI
  • Raum: MAR 4.017
  • Telefon: +4930 314-73749
  • E-Mail: manfred.opper <AT> tu-berlin.de

 

 


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Publikationen

2013

Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models

Manfred Opper and Ulrich Paquet and Ole Winther

Journal of Machine Learning Research, 2857-2898. 2013

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

Alex Susemihl and Ron Meir and Manfred Opper

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

Florian Stimberg and Manfred Opper and Andreas Ruttor

Proceedings of the International Conference on Artificial Intelligence and Statistics 2012

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Optimal control as a graphical model inference problem

Hilbert J. Kappen and Vincenc Gomez and Manfred Opper

Machine Learning. Springer, 159-182. 2012

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2011

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

Florian Stimberg and Andreas Ruttor and Manfred Opper

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

Florian Stimberg and Manfred Opper and Guido Sanguinetti and Andreas Ruttor

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

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Analytical Results for the Error in Filtering of Gaussian Processes

Alex Susemihl and Manfred Opper and Ron Meir

Advances in Neural Information Processing Systems 24. Curran Associates, Inc., 2303–2311. 2011

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Approximate inference for continuous–time Markov processes

Cédric Archambeau and Manfred Opper

Bayesian Time Series Models. Cambridge University Press, 125–140.. 2011

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Estimating parameters in stochastic systems: A variational Bayesian approach

Michail D. Vrettas and Dan Cornford and Manfred Opper

Physica D: Nonlinear Phenomena. Elsevier, 1877-1900. 2011

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Common Input Explains Higher-Order Correlations and Entropy in a Simple Model of Neural Population Activity

Jakob Macke and Manfred Opper and Matthias Bethge

Physical Review Letters. American Physical Society, 208102. 2011

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2010

Approximate inference for stochastic reaction processes

Andreas Ruttor and Guido Sanguinetti and Manfred Opper

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

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Approximate parameter inference in a stochastic reaction-diffusion model

Andreas Ruttor and Manfred Opper

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

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Approximate inference in continuous time Gaussian-Jump processes

Manfred Opper and Andreas Ruttor and Guido Sanguinetti

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

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Comparing diffusion and weak noise approximations for inference in reaction models

Andreas Ruttor and Florian Stimberg and Manfred Opper

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

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Postadresse

TU Berlin
Fakultät IV
Elektrotechnik und Informatik
Sekr. MAR 4-2
Marchsstrasse 23
D-10587 Berlin