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Inhalt des Dokuments

Prof. Dr. Manfred Opper

Lupe [1]
  • Leiter der Einheit KI
  • Raum: MAR 4.017
  • Telefon: +4930 314-73749
  • E-Mail: manfred.opper <AT> tu-berlin.de

 

 


Sprechstunde nach Vereinbarung

  • Forschungsgebiete [2]
  • Publikationen [3]
  • Lebenslauf [4]

Publikationen

<< zurück [5]
vor >> [17]

2013

Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models [21]

Manfred Opper and Ulrich Paquet and Ole Winther

Journal of Machine Learning Research, 2857-2898. 2013

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

Dynamic state estimation based on Poisson spike trains—towards a theory of optimal encoding [24]

Alex Susemihl and Ron Meir and Manfred Opper

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

Link zur Publikation [25] Download Bibtex Eintrag [26]

2012

Bayesian Inference for Change Points in Dynamical Systems with Reusable States—a Chinese Restaurant Process Approach [27]

Florian Stimberg and Manfred Opper and Andreas Ruttor

Proceedings of the International Conference on Artificial Intelligence and Statistics 2012

Link zur Publikation [28] Download Bibtex Eintrag [29]

Optimal control as a graphical model inference problem [30]

Hilbert J. Kappen and Vincenc Gomez and Manfred Opper

Machine Learning. Springer, 159-182. 2012

Link zur Publikation [31] Download Bibtex Eintrag [32]

2011

Bayesian Inference for Models of Transcriptional Regulation Using Markov Chain Monte Carlo Sampling [33]

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

Link zur Publikation [34] Download Bibtex Eintrag [35]

Inference in continuous-time change-point models [36]

Florian Stimberg and Manfred Opper and Guido Sanguinetti and Andreas Ruttor

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

Link zur Publikation [37] Download Bibtex Eintrag [38]

Analytical Results for the Error in Filtering of Gaussian Processes [39]

Alex Susemihl and Manfred Opper and Ron Meir

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

Link zur Publikation [40] Download Bibtex Eintrag [41]

Approximate inference for continuous–time Markov processes [42]

Cédric Archambeau and Manfred Opper

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

Link zur Publikation [43] Download Bibtex Eintrag [44]

Estimating parameters in stochastic systems: A variational Bayesian approach [45]

Michail D. Vrettas and Dan Cornford and Manfred Opper

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

Download Bibtex Eintrag [46]

Common Input Explains Higher-Order Correlations and Entropy in a Simple Model of Neural Population Activity [47]

Jakob Macke and Manfred Opper and Matthias Bethge

Physical Review Letters. American Physical Society, 208102. 2011

Download Bibtex Eintrag [48]

Expectation Propagation with Factorizing Distributions: A Gaussian Approximation and Performance Results for Simple Models [49]

Fabiano Ribeiro and Manfred Opper

Neural Computation. MIT Press, 1047–1069. 2011

Download Bibtex Eintrag [50]

2010

Approximate inference for stochastic reaction processes [51]

Andreas Ruttor and Guido Sanguinetti and Manfred Opper

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

Link zur Publikation [52] Download Bibtex Eintrag [53]

Approximate parameter inference in a stochastic reaction-diffusion model [54]

Andreas Ruttor and Manfred Opper

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

Link zur Publikation [55] Download Bibtex Eintrag [56]

Approximate inference in continuous time Gaussian-Jump processes [57]

Manfred Opper and Andreas Ruttor and Guido Sanguinetti

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

Link zur Publikation [58] Download Bibtex Eintrag [59]

Comparing diffusion and weak noise approximations for inference in reaction models [60]

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

Link zur Publikation [61] Download Bibtex Eintrag [62]

<< zurück [63]
vor >> [75]

Postadresse

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