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Approximate Gaussian process inference for the drift of stochastic differential equations [21]

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

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

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

A Variational Approach to Learning Curves [24]

Malzahn, D. and Opper, M.

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

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

TAP Gibbs Free Energy, Belief Propagation and Sparsity [27]

Csató, L., Opper, M. and Winther, O.

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

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

Learning curves for Gaussian processes models: Fluctuations and Universality [30]

Malzahn, D. and Opper, M.

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

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

Online Learning of Wind-Field Models [33]

Csató, L., Cornford, D. and Opper, M.

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

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

Sparse Representation for Gaussian Process Models [36]

Csató, L. and Opper, M.

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

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

Learning Curves for Gaussian processes regression: A framework for good approximations [39]

Malzahn, D. and Opper, M.

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

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

Continuous drifting games [42]

Freund, Y. and Opper, M.

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

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

Efficient Approaches to Gaussian Process Classification [45]

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

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

Link zur Publikation [46] Download Bibtex Eintrag [47]

General Bounds on Bayes errors for regression with Gaussian processes [48]

Opper, M. and Vivarelli, F.

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

Link zur Publikation [49] Download Bibtex Eintrag [50]

Mean field methods for classification with Gaussian processes [51]

Opper, M. and Winther, O.

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

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

Finite Dimensional Approximation of Gaussian Processes [54]

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

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

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

Replicator Dynamics [57]

Opper, M. and Diederich, S.

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

Download Bibtex Eintrag [58]

A mean field algorithm for Bayes learning in large feedforward neural networks [59]

Opper, M. and Winther, O.

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

Link zur Publikation [60] Download Bibtex Eintrag [61]

Dynamics of Training [62]

Bös, S. and Opper, M.

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

Link zur Publikation [63] Download Bibtex Eintrag [64]

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