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List of Publications

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Learning Rules and Learning Times in Neural Networks [21]

Opper, M.

Dynamics of Networks. Akademie Verlag Berlin, 66-75. 1989

Download Bibtex entry [22]

Statistical Mechanics of Learning in Neural Network Models [23]

Opper, M., Diederich, S. and Anlauf, J. K.

Chaos and Complexity. World Scientific, 219–223. 1987

Download Bibtex entry [24]

Wie stehe ich zur Philosophie, und was erwarte ich von ihr? (What are my views on philosophy and what do I expect from it? [25]

Opper, M.

Wege zur Philosophie (paths to philosophy). Schwabe & Co. AG, 52–56. 1980

Download Bibtex entry [26]

Expectation Consistent Free Energies for Approximate Inference [27]

Opper, M. and Winther, O.

Advances in Neural Information Processing Systems 17 2005

Link to publication [28] Download Bibtex entry [29]

Variational Linear Response [30]

Opper, M. and Winther, O.

Advances in Neural Information Processing Systems 16. MIT Press. 2004

Link to publication [31] Download Bibtex entry [32]

Asymptotic Universality for Learning Curves of Support Vector Machines [33]

Opper, M. and Urbanczik, R.

Advances in Neural Information Processing Systems 14. MIT Press, 479-486. 2002

Link to publication [34] Download Bibtex entry [35]

General Bounds on Bayes errors for regression with Gaussian processes [36]

Opper, M. and Vivarelli, F.

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

Link to publication [37] Download Bibtex entry [38]

Mean field methods for classification with Gaussian processes [39]

Opper, M. and Winther, O.

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

Link to publication [40] Download Bibtex entry [41]

Replicator Dynamics [42]

Opper, M. and Diederich, S.

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

Download Bibtex entry [43]

A mean field algorithm for Bayes learning in large feedforward neural networks [44]

Opper, M. and Winther, O.

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

Link to publication [45] Download Bibtex entry [46]

Supervised Learning: Information Theoretic Bounds on Predictive Errors [47]

Opper, M. and Haussler, D.

Proceedings of the IEEE workshop on Information Theory (ITW'95), 6.2. 1995

Link to publication [48] Download Bibtex entry [49]

Learning in Artificial Neural Networks: The Statistical Mechanics Approach [50]

Opper, M.

Supercomputing in Brain Reasearch: From Tomography to Neural Networks. World Scientific, 321–330. 1995

Download Bibtex entry [51]

Calculation of the Learning Curve of Bayes Optimal Classification Algorithm for Learning a Perceptron With Noise [52]

Opper, M. and Haussler, D.

Proceedings of the Fourth Annual Conference on Computational Learning Theory. Morgan Kaufmann, 75–87. 1991

Download Bibtex entry [53]

Statistical Mechanics of Learning in Neural Network Models [54]

Opper, M., Diederich, S. and Anlauf, J. K.

Neural Networks from Models to Applications. I.D.S.E.T., Paris, 235–243. 1988

Download Bibtex entry [55]

Statistische Mechanik des Lernens in neuronalen Netzwerken (Statistical mechanics of learning in neural networks [56]

Opper, M.

1991

Download Bibtex entry [57]

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