PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Manfred Opper

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Number of EPrints submitted by this user: 8

Variational Markov Chain Monte Carlo for Inference in Partially Observed Nonlinear Diffusions.
Yuan Shen, Cedric Archambeau, Dan Cornford and Manfred Opper
In: Proceedings of the Workshop Inference and Estimation in Probabilistic Time-Series Models, 18 - 20 June 2008, Cambridge, United Kingdom.

Improving on Expectation Propagation.
Manfred Opper, Ulrich Paquet and Ole Winther
Advances in Neural Information Processing Systems 21 2008.

Approximate inference for stochastic reaction processes.
Andreas Ruttor, Guido Sanguinetti and Manfred Opper
In: Learning and Inference in Computational Systems Biology (2009) MIT Press .

A comparison of variational and Markov Chain Monte Carlo methods for inference in partially observed stochastic dynamic systems.
Yuan Shen, Cedric Archambeau, Dan Cornford, Manfred Opper, John Shawe-Taylor and Remi Barillec
Journal of Signal Processing Systems 2009. ISSN 1939-8018 (Print) 1939-8115 (Online)

The Variational Gaussian Approximation Revisited.
Manfred Opper and Cedric Archambeau
Neural Computation Volume 21, pp. 786-792, 2009.

Switching Regulatory Models of Cellular Stress Response.
Guido Sanguinetti, Andreas Ruttor and Manfred Opper
Bioinformatics 2009.

Approximate inference in continuous time Gaussian-Jump processes
Manfred Opper, Andreas Ruttor and Guido Sanguinetti
Advances in Neural Information Processing Systems Volume 23, pp. 1831-1839, 2010.

Approximate parameter inference in a stochastic reaction-diffusion model
Andreas Ruttor and Manfred Opper
AISTATS 2010 2010.