Carl Edward Rasmussen

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Chris WilliamsProfessor of Machine Learning, University of EdinburghPreverjeni e-poštni naslov na inf.ed.ac.uk
Marc DeisenrothUniversity College London and Google DeepMindPreverjeni e-poštni naslov na ucl.ac.uk
Joaquin Quiñonero CandelaOpenAIPreverjeni e-poštni naslov na openai.com
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GooglePreverjeni e-poštni naslov na eng.cam.ac.uk
Mark van der WilkAssociate Professor, University of OxfordPreverjeni e-poštni naslov na cs.ox.ac.uk
Hannes NickischPhilips ResearchPreverjeni e-poštni naslov na philips.com
Roderick Murray-SmithProfessor of Computing Science, University of Glasgow, School of Computing SciencePreverjeni e-poštni naslov na glasgow.ac.uk
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHPreverjeni e-poštni naslov na tuebingen.mpg.de
Malte KussPreverjeni e-poštni naslov na alumni.tu-berlin.de
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIPreverjeni e-poštni naslov na ias.tu-darmstadt.de
Dilan GorurDeepMindPreverjeni e-poštni naslov na google.com
Lars Kai HansenProfessor, Cognitive Systems, DTU Compute, Technical University of DenmarkPreverjeni e-poštni naslov na dtu.dk
Roger FrigolaMachine Learning at www.rogerfrigola.comPreverjeni e-poštni naslov na rogerfrigola.com
Dieter FoxUniversity of Washington and NVIDIAPreverjeni e-poštni naslov na cs.washington.edu
Rowan McAllisterWaymoPreverjeni e-poštni naslov na waymo.com
Fabian SinzProfessor for Machine Learning, University GöttingenPreverjeni e-poštni naslov na cs.uni-goettingen.de
Jan LarsenTechnical University of Denmark, DTU ComputePreverjeni e-poštni naslov na dtu.dk
Matthew J. BealChicago Trading CompanyPreverjeni e-poštni naslov na chicagotrading.com
James HensmanMicrosoft ResearchPreverjeni e-poštni naslov na microsoft.com
Olivier BousquetGooglePreverjeni e-poštni naslov na m4x.org

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Carl Edward Rasmussen

Professor of Machine Learning, University of Cambridge

Preverjeni e-poštni naslov na cam.ac.uk - Domača stran

Gaussian processes Bayesian inference machine learning climate change


Naslov Razvrsti po navedbah Razvrsti po letniku Razvrsti po naslovu	Navedeno Navedeno	Leto
Gaussian Processes for Machine Learning CE Rasmussen, CKI Williams the MIT Press, 2006	37105	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	2680	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	2153	2011
Gaussian processes for regression CKI Williams, CE Rasmussen Advances in Neural Processing Systems 8, 514 - 520, 1996	2082	1996
The infinite Gaussian mixture model CE Rasmussen Advances in neural information processing systems 12, 1999	1895	1999
Gaussian processes for machine learning (GPML) toolbox CE Rasmussen, H Nickisch The Journal of Machine Learning Research 11, 3011-3015, 2010	1357	2010
The infinite hidden Markov model MJ Beal, Z Ghahramani, CE Rasmussen Advances in neural information processing systems 14, 577-584, 2002	898	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	893	2015
Advances in neural information processing systems CKI Williams, CE Rasmussen Nobili F, Mazzei D, Dessi B, Morbelli S, Brugnolo A, Barbieri P, 18131821, 1996	880	1996
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	696*	2003
Infinite mixtures of Gaussian process experts CE Rasmussen, Z Ghahramani Advances in neural information processing systems 14 2, 881-888, 2002	687	2002
Evaluation of Gaussian processes and other methods for non-linear regression CE Rasmussen University of Toronto Toronto, Canada, 1997	677	1997
Sparse spectrum Gaussian process regression M Lázaro-Gredilla, J Quiñonero-Candela, CE Rasmussen, ... The Journal of Machine Learning Research 11, 1865-1881, 2010	622	2010
Approximations for binary Gaussian process classification H Nickisch, CE Rasmussen Journal of Machine Learning Research 9 (10), 2035-2078, 2008	512	2008
Warped Gaussian processes E Snelson, CE Rasmussen, Z Ghahramani Advances in neural information processing systems 16, 337-344, 2004	482	2004
Gaussian Processes in Machine Learning CE Rasmussen Summer school on machine learning, 63-71, 2003	481*	2003
Additive Gaussian Processes D Duvenaud, H Nickisch, CE Rasmussen Neural Information Processing Systems 24, 226-234, 2012	458	2012
Derivative observations in Gaussian process models of dynamic systems E Solak, R Murray-Smith, WE Leithead, DJ Leith, CE Rasmussen MIT Press, 2003	437	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	423	2000

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