Publikationen von M Kuss

Kuss, M.; Rasmussen, C.: Assessing Approximate Inference for Binary Gaussian Process Classification. The Journal of Machine Learning Research 6, S. 1679 - 1704 (2005)

Kuss, M.; Jäkel, F.; Wichmann, F.: Bayesian inference for psychometric functions. Journal of Vision 5 (5), 8, S. 478 - 492 (2005)

Kuss, M.; Rasmussen, C.: Assessing Approximations for Gaussian Process Classification. In: Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference, S. 699 - 706 (Hg. Weiss, Y.; Schölkopf, B.; Platt, J.). Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005), Whistler, BC, Canada, 05. Dezember 2005 - 08. Dezember 2005. MIT Press, Cambridge, MA, USA (2006)

Eichhorn, J.; Tolias, A.; Zien, A.; Kuss, M.; Rasmussen, C.; Weston, J.; Logothetis, N.; Schölkopf, B.: Prediction on Spike Data Using Kernel Algorithms. In: Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference, S. 1367 - 1374 (Hg. Thrun, S.; Saul, L.; Schölkopf, B.). Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, 08. Dezember 2003 - 13. Dezember 2003. MIT Press, Cambridge, MA, USA (2004)

Rasmussen, C.; Kuss, M.: Gaussian Processes in Reinforcement Learning. In: Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference, S. 751 - 759 (Hg. Thrun, S.; Saul, L.; Schölkopf, B.). Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, 08. Dezember 2003 - 13. Dezember 2003. MIT Press, Cambridge, MA, USA (2004)

Pfingsten, T.; Kuss, M.; Rasmussen, C.: Nonstationary Gaussian Process Regression using a Latent Extension of the Input Space. Eighth World Meeting of the International Society for Bayesian Analysis (ISBA 2006), Benidorm, Spain (2006)

Kuss, M.; Jäkel, F.; Wichmann, F.: Bayesian Inference for Psychometric Functions. 8th Tübinger Wahrnehmungskonferenz (TWK 2005), Tübingen, Germany (2005)

Kuss, M.: Gaussian Process Models for Robust Regression, Classification, and Reinforcement Learning. Dissertation, 205 S., echnische Universität Darmstadt, Darmstadt, Germany (2006)

Kuss, M.: Nonlinear Multivariate Analysis with Geodesic Kernels. Diplom, Technische Universität Berlin, Berlin, Germany (2002)

Kuss, M.; Pfingsten, T.; Csato, L.; Rasmussen, C.: Approximate Inference for Robust Gaussian Process Regression (Technical Report of the Max Planck Institute for Biological Cybernetics, 136). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2005), 27 S.

Kuss, M.; Jäkel, F.; Wichmann, F.: Approximate Bayesian Inference for Psychometric Functions using MCMC Sampling (Technical Report of the Max Planck Institute for Biological Cybernetics, 135). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2005), 30 S.

Kuss, M.; Graepel, T.: The Geometry Of Kernel Canonical Correlation Analysis (Technical Report of the Max Planck Institute for Biological Cybernetics, 108). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2003), 11 S.