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C

Bayesian Analysis of the Scatterometer Wind Retrieval inverse Problem: Some new Approaches [21]

Cornford, D., Csató, L., Evans, D. J. and Opper, M.

Journal Royal Statistical Society B, 1–17. 2004

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

Sparse Gaussian processes: inference,subspace identification and model selection [24]

Csató, L. and Opper, M.

Proceedings of SYSID 2003, 1 - 6. 2003

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

Data Assimilation with Sequential Gaussian Processes [27]

Csató, L., Cornford, D. and Opper, M.

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

Download Bibtex Eintrag [28]

TAP Gibbs Free Energy, Belief Propagation and Sparsity [29]

Csató, L., Opper, M. and Winther, O.

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

Link zur Publikation [30] Download Bibtex Eintrag [31]

Online Learning of Wind-Field Models [32]

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 [33] Download Bibtex Eintrag [34]

Sparse Representation for Gaussian Process Models [35]

Csató, L. and Opper, M.

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

Link zur Publikation [36] Download Bibtex Eintrag [37]

Efficient Approaches to Gaussian Process Classification [38]

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 [39] Download Bibtex Eintrag [40]

Tractable Inference for Probabilistic Data Models [41]

Csató, L., Opper, M. and Winther, O.

Complexity, 64-68. 2003

Link zur Publikation [42] Download Bibtex Eintrag [43]

Sparse On-Line Gaussian Processes [44]

Csató, L. and Opper, M.

Neural Computation, 641 - 668. 2002

Link zur Publikation [45] Download Bibtex Eintrag [46]

Expectation propagation for continuous time stochastic processes [47]

Cseke, B., Schnoerr, D., Opper, M. and Sanguinetti, G.

Journal of Physics A: Mathematical and Theoretical. IOPscience, 494002. 2016

Link zur Publikation [48] Download Bibtex Eintrag [49]

Approximate inference in latent Gaussian-Markov models from continuous time observations [50]

Cseke, B., Opper, M. and Sanguinetti, G.

Advances in Neural Information Processing Systems, 971–979. 2013

Link zur Publikation [51] Download Bibtex Eintrag [52]

D

Replicators with Random Interactions- a Solvable Model [53]

Diederich, S. and Opper, M.

Phys. Rev. A (Rapid Comm.), 4333. 1989

Download Bibtex Eintrag [54]

Learning of Correlated Patterns in Spin- Glass Networks by Local Learning Rules [55]

Diederich, S. and Opper, M.

Phys. Rev. Lett., 949–952. 1987

Download Bibtex Eintrag [56]

Learning by Error Correction in Spin Glass Models of Neural Networks [57]

Diederich, S., Opper, M., Henkel, R. D. and Kinzel, W.

Computer Simulations in Brain Science. Cambridge University Press. 1988

Download Bibtex Eintrag [58]

Calculating eddy currents for turbomolecular pumps in magnetic fields [59]

Diederich, S. and Opper, M.

1985

Download Bibtex Eintrag [60]

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