Carl Edward Rasmussen
Carl Edward Rasmussen
Professor of Machine Learning, University of Cambridge
Verified email at cam.ac.uk - Homepage
TitleCited byYear
Gaussian processes in machine learning
CE Rasmussen
Advanced Lectures on Machine Learning, 63-71, 2004
147092004
Gaussian Processes for Machine Learning
CE Rasmussen, CKI Williams
the MIT Press, 2006
146832006
The infinite hidden Markov model
MJ Beal, Z Ghahramani, CE Rasmussen
Advances in neural information processing systems 14, 577-584, 2002
2053*2002
A unifying view of sparse approximate Gaussian process regression
J Quiñonero-Candela, CE Rasmussen
The Journal of Machine Learning Research 6, 1939-1959, 2005
11592005
The infinite Gaussian mixture model
CE Rasmussen
Advances in neural information processing systems 12, 554-560, 2000
11012000
Gaussian processes for regression
CKI Williams, CE Rasmussen
Advances in Neural Processing Systems 8, 514 - 520, 1996
9841996
PILCO: A model-based and data-efficient approach to policy search
M Deisenroth, CE Rasmussen
Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011
5452011
Gaussian processes for machine learning (GPML) toolbox
CE Rasmussen, H Nickisch
The Journal of Machine Learning Research 11, 3011-3015, 2010
5152010
Evaluation of Gaussian processes and other methods for non-linear regression
CE Rasmussen
University of Toronto, 1996
4971996
Infinite mixtures of Gaussian process experts
CE Rasmussen, Z Ghahramani
Advances in neural information processing systems 14 2, 881-888, 2002
4072002
Gaussian Process priors with uncertain inputs - Application to multiple-step ahead time series forecasting
A Girard, CE Rasmussen, J Quinonero-Candela, R Murray-Smith
MIT Press, 2003
384*2003
Gaussian process priors with uncertain inputs: Multiple-step ahead prediction
A Girard, CE Rasmussen, R Murray-Smith
Delovno porocilo DCS TR-2002-119, University of Glasgow, Glasgow, 2002
320*2002
Gaussian Processes for Data-Efficient Learning in Robotics and Control
M Deisenroth, D Fox, C Rasmussen
IEEE Transactions on Pattern Analysis and Machine Intelligence 37, 408-423, 2015
2922015
Assessing approximate inference for binary Gaussian process classification
M Kuss, CE Rasmussen
The Journal of Machine Learning Research 6, 1679-1704, 2005
2922005
Approximations for binary Gaussian process classification
H Nickisch, CE Rasmussen
Journal of Machine Learning Research 9, 2035-2078, 2008
2742008
Sparse spectrum Gaussian process regression
M Lázaro-Gredilla, J Quiñonero-Candela, CE Rasmussen, ...
The Journal of Machine Learning Research 11, 1865-1881, 2010
248*2010
Warped Gaussian processes
E Snelson, CE Rasmussen, Z Ghahramani
Advances in neural information processing systems 16, 337-344, 2004
2272004
Gaussian Processes in Reinforcement Learning
M Kuss, CE Rasmussen
Advances in Neural Information Processing Systems, None, 2003
2192003
Derivative observations in Gaussian process models of dynamic systems
E Solak, R Murray-Smith, WE Leithead, DJ Leith, CE Rasmussen
MIT Press, 2003
2172003
Bayesian monte Carlo
CE Rasmussen, Z Ghahramani
Advances in neural information processing systems 15, 489-496, 2003
214*2003
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