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Approximate inference in continuous time Gaussian-Jump processes

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

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

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Parameter estimation and inference for stochastic reaction-diffusion systems: application to morphogenesis in D. melanogaster

Opper, M., Dewar, M. A., Kadirkamanathan, V. and Sanguinetti, G.

BMC Systems Biology. BMC Systems Biology %, 669 - 676. 2010

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A new variational radial basis function approximation for inference in multivariate diffusions

Opper, M., Vrettas, M. D. and Cornford, D.

Neurocomputing. Elsevier, 1186 - 1198. 2010

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Learning combinatorial transcriptional dynamics from gene expression data

Opper, M. and Sanguinetti, G.

Bioinformatics. Oxford Journals, 1623-1629. 2010

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A theory of solving TAP equations for Ising models with general invariant random matrices

Opper, M., Cakmak, B. and Winther, O.

Journal of Physics A: Mathematical and Theoretical, 114002. 2016

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Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models

Opper, M., Paquet, U. and Winther, O.

Journal of Machine Learning Research, 2857-2898. 2013

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Expectation Consistent Approximate Inference

Opper, M. and Winther, O.

Journal of Machine Learning Research, 2177 - 2204. 2005

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Adaptive and Selfaveraging TAP Mean Field Theory

Opper, M. and Winther, O.

Physical Review E, 056131. 2001

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Universal learning curves of support vector machines

Opper, M. and Urbanczik, R.

Phys. Rev. Lett., 4410-4413. 2001

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Probabilistic data modelling with adaptive TAP mean field theory

Opper, M. and Winther, O.

Second Minerva Workshop on Frontiers in the Physics of Complex Systems, 119-125. 2001

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Support Vector machines learning noisy polynomial rules

Opper, M. and Urbanczik, R.

Second Minerva Workshop on Frontiers in the Physics of Complex Systems, 110-118. 2001

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