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Approximate inference techniques with expectation constraints

Heskes, T., Opper, M., Wiegerinck, W., Winther, O. and Zoeter, O.

Journal of Statistical Mechanics (JSTAT) 2005

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Retarded Learning: Rigorous Results from Statistical Mechanics

Herschkowitz, D. and Opper, M.

Phys. Rev. Lett., 2174-2177. 2001

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Distribution of Internal Fields and Dynamics of Neural Networks

Henkel, R. D. and Opper, M.

Europhys. Lett., 403–408. 1990

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Metric Entropy and Minimax Risk in Classification

Haussler, D. and Opper, M.

Lecture Notes in Computer Science: Studies in Logic and Computer Science, Vol. 1261. Springer, 212-235. 1997

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Mutual Information and Bayes Methods for Learning a Distribution

Haussler, D. and Opper, M.

Theory of Neural Networks, The Statistical Mechanics Perspective. World Scientific, 42–50. 1995

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General Bounds on the Mutual Information Between a Parameter and $n$ Conditionally Independent Observations

Haussler, D. and Opper, M.

Proceedings of the Eighth Annual Conference on Computational Learning Theory. ACM Press, 402-411. 1995

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Estimating Average - Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods

Haussler, D., Kearns, M., Opper, M. and Schapire, R. E.

Advances in Neural Information Processing Systems 4. Morgan Kaufmann, 855–862. 1992

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A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding

Harel, Y., Meir, R. and Opper, M.

Advances in Neural Information Processing Systems 28, 1594–1602. 2015

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