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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]

Gaussian Process Approximations of Stochastic Differential Equations [27]

Archambeau, C., Cornford, D., Opper, M. and Shawe-Taylor, J.

Journal of Machine Learning Research: Workshop and Conference Proceedings, 1:1–16. 2007

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

Expectation Consistent Free Energies for Approximate Inference [30]

Opper, M. and Winther, O.

Advances in Neural Information Processing Systems 17 2005

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

Approximate Analytical Bootstrap Averages for Support Vector Classifiers [33]

Malzahn, D. and Opper, M.

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

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

Variational Linear Response [36]

Opper, M. and Winther, O.

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

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

A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages [39]

Malzahn, D. and Opper, M.

Advances in Neural Information Processing Systems 15. MIT Press, 327-334. 2003

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

Sparse Gaussian processes: inference,subspace identification and model selection [42]

Csató, L. and Opper, M.

Proceedings of SYSID 2003, 1 - 6. 2003

Link to publication [43] Download Bibtex entry [44]

Data Assimilation with Sequential Gaussian Processes [45]

Csató, L., Cornford, D. and Opper, M.

Uncertainty in geometrical computation, published by: Kluwer. Kluwer, 29-40. 2002

Download Bibtex entry [46]

Approximate Gaussian process inference for the drift of stochastic differential equations - Supplementary material [47]

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

2013

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

Asymptotic Universality for Learning Curves of Support Vector Machines [50]

Opper, M. and Urbanczik, R.

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

Link to publication [51] Download Bibtex entry [52]

Approximate Gaussian process inference for the drift of stochastic differential equations [53]

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

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

Link to publication [54] Download Bibtex entry [55]

A Variational Approach to Learning Curves [56]

Malzahn, D. and Opper, M.

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

Link to publication [57] Download Bibtex entry [58]

TAP Gibbs Free Energy, Belief Propagation and Sparsity [59]

Csató, L., Opper, M. and Winther, O.

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

Link to publication [60] Download Bibtex entry [61]

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