| Assessing Approximate Inference for Binary Gaussian Process Classification. M Kuss, CE Rasmussen, R Herbrich Journal of machine learning research 6 (10), 2005 | 427 | 2005 |
| Gaussian processes in reinforcement learning M Kuss, C Rasmussen Advances in neural information processing systems 16, 2003 | 360 | 2003 |
| Gaussian process models for robust regression, classification, and reinforcement learning M Kuss Technische Universität Darmstadt, Germany, 2006 | 238 | 2006 |
| Bayesian inference for psychometric functions M Kuss, F Jäkel, FA Wichmann Journal of Vision 5 (5), 8-8, 2005 | 192 | 2005 |
| The geometry of kernel canonical correlation analysis M Kuss, T Graepel Max Planck Institute for Biological Cybernetics, 2003 | 121 | 2003 |
| Assessing approximations for Gaussian process classification M Kuss, C Rasmussen Advances in neural information processing systems 18, 2005 | 59 | 2005 |
| Prediction on spike data using kernel algorithms J Eichhorn, A Tolias, A Zien, M Kuss, J Weston, N Logothetis, B Schölkopf, ... Advances in neural information processing systems 16, 2003 | 44 | 2003 |
| Nonstationary gaussian process regression using a latent extension of the input space T Pfingsten, M Kuss, CE Rasmussen Eighth World Meeting of the International Society for Bayesian Analysis …, 2006 | 35 | 2006 |
| Approximate inference for robust Gaussian process regression M Kuss, T Pfingsten, L Csató, CE Rasmussen Max Planck Institute for Biological Cybernetics, 2005 | 27 | 2005 |
| Approximate Bayesian inference for psychometric functions using MCMC sampling M Kuss, F Jäkel, FA Wichmann Max Planck Institute for Biological Cybernetics, 2005 | 4 | 2005 |
| Nonlinear Multivariate Analysis with Geodesic Kernels M Kuss Technische Universität Berlin, 2002 | 4 | 2002 |
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
