Carl Edward Rasmussen

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Chris WilliamsProfessor of Machine Learning, University of EdinburghVerificeret mail på inf.ed.ac.uk
Marc DeisenrothUniversity College LondonVerificeret mail på ucl.ac.uk
Joaquin Quiñonero CandelaOpenAIVerificeret mail på openai.com
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerificeret mail på eng.cam.ac.uk
Mark van der WilkAssociate Professor, University of OxfordVerificeret mail på cs.ox.ac.uk
Roderick Murray-SmithProfessor of Computing Science, University of Glasgow, School of Computing ScienceVerificeret mail på glasgow.ac.uk
Hannes NickischPhilips ResearchVerificeret mail på philips.com
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHVerificeret mail på tuebingen.mpg.de
Malte KussVerificeret mail på alumni.tu-berlin.de
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIVerificeret mail på ias.tu-darmstadt.de
Dilan GorurDeepMindVerificeret mail på google.com
Lars Kai HansenProfessor, Cognitive Systems, DTU Compute, Technical University of DenmarkVerificeret mail på dtu.dk
Roger FrigolaMachine Learning at www.rogerfrigola.comVerificeret mail på rogerfrigola.com
Dieter FoxUniversity of Washington and NVIDIAVerificeret mail på cs.washington.edu
Fabian SinzProfessor for Machine Learning, University GöttingenVerificeret mail på cs.uni-goettingen.de
Rowan McAllisterWaymoVerificeret mail på waymo.com
Jan LarsenTechnical University of Denmark, DTU ComputeVerificeret mail på dtu.dk
Matthew J. BealChicago Trading CompanyVerificeret mail på chicagotrading.com
James HensmanMicrosoft ResearchVerificeret mail på microsoft.com
Olivier BousquetGoogleVerificeret mail på m4x.org

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Carl Edward Rasmussen

Professor of Machine Learning, University of Cambridge

Verificeret mail på cam.ac.uk - Startside

Gaussian processes Bayesian inference machine learning climate change


Titel Sortér efter henvisninger Sortér efter årstal Sortér efter titel	Citeret af Citeret af	År
Gaussian Processes for Machine Learning CE Rasmussen, CKI Williams the MIT Press, 2006	36306	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	2628	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	2086	2011
Gaussian processes for regression CKI Williams, CE Rasmussen Advances in Neural Processing Systems 8, 514 - 520, 1996	2005	1996
The infinite Gaussian mixture model CE Rasmussen Advances in neural information processing systems 12, 1999	1873	1999
Gaussian processes for machine learning (GPML) toolbox CE Rasmussen, H Nickisch The Journal of Machine Learning Research 11, 3011-3015, 2010	1322	2010
The infinite hidden Markov model MJ Beal, Z Ghahramani, CE Rasmussen Advances in neural information processing systems 14, 577-584, 2002	895	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	880	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	677*	2003
Infinite mixtures of Gaussian process experts CE Rasmussen, Z Ghahramani Advances in neural information processing systems 14 2, 881-888, 2002	676	2002
Evaluation of Gaussian processes and other methods for non-linear regression CE Rasmussen University of Toronto Toronto, Canada, 1997	674	1997
Sparse spectrum Gaussian process regression M Lázaro-Gredilla, J Quiñonero-Candela, CE Rasmussen, ... The Journal of Machine Learning Research 11, 1865-1881, 2010	613	2010
Approximations for binary Gaussian process classification H Nickisch, CE Rasmussen Journal of Machine Learning Research 9 (Oct), 2035-2078, 2008	506	2008
Warped Gaussian processes E Snelson, CE Rasmussen, Z Ghahramani Advances in neural information processing systems 16, 337-344, 2004	472	2004
Gaussian Processes in Machine Learning CE Rasmussen Summer school on machine learning, 63-71, 2003	468*	2003
Additive Gaussian Processes D Duvenaud, H Nickisch, CE Rasmussen Neural Information Processing Systems 24, 226-234, 2012	440	2012
Derivative observations in Gaussian process models of dynamic systems E Solak, R Murray-Smith, WE Leithead, DJ Leith, CE Rasmussen MIT Press, 2003	432	2003
Assessing Approximate Inference for Binary Gaussian Process Classification. M Kuss, CE Rasmussen Journal of machine learning research 6 (10), 2005	427	2005
Occam's razor C Rasmussen, Z Ghahramani Advances in neural information processing systems 13, 2000	416	2000
Bayesian monte Carlo CE Rasmussen, Z Ghahramani Advances in neural information processing systems 15, 489-496, 2003	382*	2003

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