Search Machine Learning Repository:
All publications by Carl E. Rasmussen
authors venues years



Active Learning of Model Evidence Using Bayesian Quadrature
Michael Osborne, Roman Garnett, Zoubin Ghahramani, David K. Duvenaud, Stephen J. Roberts and Carl E. Rasmussen
Advances in Neural Information Processing Systems 25, 2012


Gaussian Processes for time-marked time-series data
John Cunningham, Zoubin Ghahramani and Carl E. Rasmussen
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Gaussian Process Training with Input Noise
Andrew Mchutchon and Carl E. Rasmussen
Advances in Neural Information Processing Systems 24, 2011


Additive Gaussian Processes
David K. Duvenaud, Hannes Nickisch and Carl E. Rasmussen
Advances in Neural Information Processing Systems 24, 2011


PILCO: A Model-Based and Data-Efficient Approach to Policy Search
Marc Deisenroth and Carl E. Rasmussen
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Gaussian Process Change Point Models
Yunus Saatci, Ryan D. Turner and Carl E. Rasmussen
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


State-Space Inference and Learning with Gaussian Processes
Ryan D. Turner, Marc P. Deisenroth and Carl E. Rasmussen
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


The Need for Open Source Software in Machine Learning
Sören Sonnenburg, Mikio L. Braun, Cheng S. Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann Lecun, Klaus-robert Müller, Fernando Pereira, Carl E. Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Pascal Vincent, Jason Weston, Robert C. Williamson and Alex J. Smola
Journal of Machine Learning Research, 2007


A choice model with infinitely many latent features
Dilan Görür, Frank Jäkel and Carl E. Rasmussen
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Healing the relevance vector machine through augmentation
Carl E. Rasmussen and Joaquin Q. Candela
Proceedings of the 22nd International Conference on Machine Learning (ICML-05), 2005


Assessing Approximations for Gaussian Process Classification
Malte Kuss and Carl E. Rasmussen
Advances in Neural Information Processing Systems 18, 2005


Assessing Approximate Inference for Binary Gaussian Process Classification
Malte Kuss and Carl E. Rasmussen
Journal of Machine Learning Research, 2005


A Unifying View of Sparse Approximate Gaussian Process Regression
Joaquin Q. Candela and Carl E. Rasmussen
Journal of Machine Learning Research, 2005


Prediction on Spike Data Using Kernel Algorithms
Jan Eichhorn, Andreas Tolias, Alexander Zien, Malte Kuss, Jason Weston, Nikos Logothetis, Bernhard Schölkopf and Carl E. Rasmussen
Advances in Neural Information Processing Systems 16, 2003


Gaussian Processes in Reinforcement Learning
Malte Kuss and Carl E. Rasmussen
Advances in Neural Information Processing Systems 16, 2003


Warped Gaussian Processes
Edward Snelson, Zoubin Ghahramani and Carl E. Rasmussen
Advances in Neural Information Processing Systems 16, 2003


Derivative Observations in Gaussian Process Models of Dynamic Systems
E. Solak, R. Murray-smith, W. E. Leithead, D. J. Leith and Carl E. Rasmussen
Advances in Neural Information Processing Systems 15, 2002


Gaussian Process Priors with Uncertain Inputs -- Application to Multiple-Step Ahead Time Series Forecasting
Agathe Girard, Joaquin Q. Candela, Roderick Murray-smith and Carl E. Rasmussen
Advances in Neural Information Processing Systems 15, 2002


Bayesian Monte Carlo
Zoubin Ghahramani and Carl E. Rasmussen
Advances in Neural Information Processing Systems 15, 2002


Infinite Mixtures of Gaussian Process Experts
Carl E. Rasmussen and Zoubin Ghahramani
Advances in Neural Information Processing Systems 14, 2001


The Infinite Hidden Markov Model
Matthew J. Beal, Zoubin Ghahramani and Carl E. Rasmussen
Advances in Neural Information Processing Systems 14, 2001