Carl Edward Rasmussen

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Chris WilliamsProfessor of Machine Learning, University of EdinburghAdresse e-mail validée de inf.ed.ac.uk
Marc DeisenrothUniversity College London and Google DeepMindAdresse e-mail validée de ucl.ac.uk
Joaquin Quiñonero CandelaOpenAIAdresse e-mail validée de openai.com
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleAdresse e-mail validée de eng.cam.ac.uk
Mark van der WilkAssociate Professor, University of OxfordAdresse e-mail validée de cs.ox.ac.uk
Roderick Murray-SmithProfessor of Computing Science, University of Glasgow, School of Computing ScienceAdresse e-mail validée de glasgow.ac.uk
Hannes NickischPhilips ResearchAdresse e-mail validée de philips.com
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHAdresse e-mail validée de tuebingen.mpg.de
Malte KussAdresse e-mail validée de alumni.tu-berlin.de
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIAdresse e-mail validée de ias.tu-darmstadt.de
Dilan GorurDeepMindAdresse e-mail validée de google.com
Lars Kai HansenProfessor, Cognitive Systems, DTU Compute, Technical University of DenmarkAdresse e-mail validée de dtu.dk
Roger FrigolaMachine Learning at www.rogerfrigola.comAdresse e-mail validée de rogerfrigola.com
Dieter FoxUniversity of Washington and NVIDIAAdresse e-mail validée de cs.washington.edu
Rowan McAllisterWaymoAdresse e-mail validée de waymo.com
Fabian SinzProfessor for Machine Learning, University GöttingenAdresse e-mail validée de cs.uni-goettingen.de
Jan LarsenTechnical University of Denmark, DTU ComputeAdresse e-mail validée de dtu.dk
Matthew J. BealChicago Trading CompanyAdresse e-mail validée de chicagotrading.com
James HensmanMicrosoft ResearchAdresse e-mail validée de microsoft.com
Olivier BousquetGoogleAdresse e-mail validée de m4x.org

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Carl Edward Rasmussen

Professor of Machine Learning, University of Cambridge

Adresse e-mail validée de cam.ac.uk - Page d'accueil

Gaussian processes Bayesian inference machine learning climate change


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Gaussian Processes for Machine Learning CE Rasmussen, CKI Williams the MIT Press, 2006	36981	2006
A unifying view of sparse approximate Gaussian process regression J Quiñonero-Candela, CE Rasmussen The Journal of Machine Learning Research 6, 1939-1959, 2005	2671	2005
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	2138	2011
Gaussian processes for regression CKI Williams, CE Rasmussen Advances in Neural Processing Systems 8, 514 - 520, 1996	2060	1996
The infinite Gaussian mixture model CE Rasmussen Advances in neural information processing systems 12, 1999	1897	1999
Gaussian processes for machine learning (GPML) toolbox CE Rasmussen, H Nickisch The Journal of Machine Learning Research 11, 3011-3015, 2010	1347	2010
The infinite hidden Markov model MJ Beal, Z Ghahramani, CE Rasmussen Advances in neural information processing systems 14, 577-584, 2002	900	2002
Gaussian Processes for Data-Efficient Learning in Robotics and Control M Deisenroth, D Fox, CE Rasmussen IEEE Transactions on Pattern Analysis and Machine Intelligence 37, 408-423, 2015	896	2015
Gaussian Process priors with uncertain inputs - Application to multiple-step ahead time series forecasting A Girard, CE Rasmussen, J Quinonero-Candela, R Murray-Smith Neural Information Processing Systems (NIPS), 545-552, 2003	692*	2003
Infinite mixtures of Gaussian process experts CE Rasmussen, Z Ghahramani Advances in neural information processing systems 14 2, 881-888, 2002	683	2002
Evaluation of Gaussian processes and other methods for non-linear regression CE Rasmussen University of Toronto Toronto, Canada, 1997	676	1997
Sparse spectrum Gaussian process regression M Lázaro-Gredilla, J Quiñonero-Candela, CE Rasmussen, ... The Journal of Machine Learning Research 11, 1865-1881, 2010	626	2010
Approximations for binary Gaussian process classification H Nickisch, CE Rasmussen Journal of Machine Learning Research 9 (Oct), 2035-2078, 2008	515	2008
Gaussian Processes in Machine Learning CE Rasmussen Summer school on machine learning, 63-71, 2003	484*	2003
Warped Gaussian processes E Snelson, CE Rasmussen, Z Ghahramani Advances in neural information processing systems 16, 337-344, 2004	481	2004
Additive Gaussian Processes D Duvenaud, H Nickisch, CE Rasmussen Neural Information Processing Systems 24, 226-234, 2012	449	2012
Derivative observations in Gaussian process models of dynamic systems E Solak, R Murray-Smith, WE Leithead, DJ Leith, CE Rasmussen MIT Press, 2003	440	2003
Assessing Approximate Inference for Binary Gaussian Process Classification. M Kuss, CE Rasmussen Journal of machine learning research 6 (10), 2005	430	2005
Occam's razor C Rasmussen, Z Ghahramani Advances in neural information processing systems 13, 2000	421	2000
Bayesian monte Carlo CE Rasmussen, Z Ghahramani Advances in neural information processing systems 15, 489-496, 2003	391*	2003

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