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Inhalt des Dokuments

Publikationsliste

Approximate Gaussian process inference for the drift of stochastic differential equations

Ruttor, A., Batz, P. and Opper, M.

Advances in Neural Information Processing Systems, 2040-2048. 2013

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A Variational Approach to Learning Curves

Malzahn, D. and Opper, M.

Advances in Neural Information Processing Systems 14. MIT Press, 463-469. 2002

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TAP Gibbs Free Energy, Belief Propagation and Sparsity

Csató, L., Opper, M. and Winther, O.

Advances in Neural Information Processing Systems 14. MIT Press, 657-663. 2002

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Learning curves for Gaussian processes models: Fluctuations and Universality

Malzahn, D. and Opper, M.

Proceedings of the International Conference on Artificial Neural Networks 2001. Springer–Verlag, 271-276. 2001

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Online Learning of Wind-Field Models

Csató, L., Cornford, D. and Opper, M.

Proceedings of the International Conference on Artificial Neural Networks 2001. Springer–Verlag, 300-307. 2001

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Sparse Representation for Gaussian Process Models

Csató, L. and Opper, M.

Advances in Neural Information Processing Systems 13. MIT Press, 444-450. 2001

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Learning Curves for Gaussian processes regression: A framework for good approximations

Malzahn, D. and Opper, M.

Advances in Neural Information Processing Systems 13. MIT Press, 273-279. 2001

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Continuous drifting games

Freund, Y. and Opper, M.

Proceedings of the Thirteenth Annual Conference on Computational Learning Theory. Morgan Kaufmann, 126-132. 2000

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Efficient Approaches to Gaussian Process Classification

Csató, L., Fokou´e, E., Opper, M., Schottky, B. and Winther, O.

Advances in Neural Information Processing Systems 12. MIT Press, 251-257. 2000

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General Bounds on Bayes errors for regression with Gaussian processes

Opper, M. and Vivarelli, F.

Advances in Neural Information Processing Systems 11. MIT Press, 302-308. 1999

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Mean field methods for classification with Gaussian processes

Opper, M. and Winther, O.

Advances in Neural Information Processing Systems 11. MIT Press, 309-315. 1999

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Finite Dimensional Approximation of Gaussian Processes

Trecate, G. F., Williams, C. K. and Opper, M.

Advances in Neural Information Processing Systems 11. MIT Press, 218-224. 1999

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Replicator Dynamics

Opper, M. and Diederich, S.

Proceedings of the Europhysics Conference on Computational Physics CCP 1998. Elsevier Science, 141-144. 1999

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A mean field algorithm for Bayes learning in large feedforward neural networks

Opper, M. and Winther, O.

Advances in Neural Information Processing Systems 9. MIT Press, 225-231. 1997

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Dynamics of Training

Bös, S. and Opper, M.

Advances in Neural Information Processing Systems 9. MIT Press, 141-147. 1997

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