Carl Edward Rasmussen - Google Scholar Citations

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Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerified email at eng.cam.ac.uk
Marc DeisenrothUniversity College LondonVerified email at ucl.ac.uk
Joaquin Quiñonero CandelaEngineering Director at FacebookVerified email at fb.com
Roderick Murray-SmithProfessor of Computing Science, University of Glasgow, School of Computing ScienceVerified email at glasgow.ac.uk
Chris WilliamsProfessor of Machine Learning, University of EdinburghVerified email at inf.ed.ac.uk
Hannes NickischSenior Scientist at Philips ResearchVerified email at philips.com
Jan PetersProfessor at Technische Universität Darmstadt and Researcher at MPI for Intelligent SystemsVerified email at ias.tu-darmstadt.de
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; and Distinguished Amazon ScholarVerified email at tuebingen.mpg.de
Dilan GorurDeepMindVerified email at google.com
Lars Kai HansenProfessor, Cognitive Systems, DTU Compute, Technical University of DenmarkVerified email at dtu.dk
Roger FrigolaMachine Learning at www.rogerfrigola.comVerified email at rogerfrigola.com
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Fabian SinzGroup Leader, University TübingenVerified email at uni-tuebingen.de
Robert C. WilliamsonProfessor of Computer Science, Australian National University; Distinguished Researcher, DATA61Verified email at anu.edu.au
Samy BengioResearch Scientist, Google BrainVerified email at google.com
Cheng Soon OngData61, CSIRO, CanberraVerified email at anu.edu.au
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleVerified email at cs.toronto.edu
Volker TrespLudwig Maximilian University of Munich / München (LMU) and Siemens AGVerified email at dbs.ifi.lmu.de
Roberto CalandraFacebook AI ResearchVerified email at fb.com
Miguel Lázaro-GredillaSenior researcher, Vicarious AIVerified email at vicarious.com

Carl Edward Rasmussen

Professor of Machine Learning, University of Cambridge

Verified email at cam.ac.uk - Homepage

Bayesian inference machine learning


Title	Cited by	Year
A Bayesian approach to modeling uncertainty in gene expression clusters DL Wild, CE Rasmussen, Z Ghahramani, J Cregg, BJ de la Cruz, CC Kan, ... 3rd International Conference on Systems Biology, Stockholm, Sweden, 2002	8	2002
A Bayesian Perspec\ ve on Sta\ s\ cal Learning Theory Z Ghahramani, C Rasmussen
A case based comparison of identification with neural network and Gaussian process models J Kocijan, B Likar, B Banko, A Girard, R Murray-Smith, CE Rasmussen Preprints of IFAC ICONS Conference, Faro, 137-142, 2003	28	2003
A choice model with infinitely many latent features D Görür, F Jäkel, CE Rasmussen Proceedings of the 23rd international conference on Machine learning, 361-368, 2006	61	2006
A Practical and Conceptual Framework for Learning in Control M Deisenroth, CE Rasmussen University of Washington, 2010	2	2010
A practical Monte Carlo implementation of Bayesian learning CE Rasmussen Advances in Neural Information Processing Systems, 598-604, 1996	28	1996
A unifying view of sparse approximate Gaussian process regression J Quiñonero-Candela, CE Rasmussen The Journal of Machine Learning Research 6, 1939-1959, 2005	1252	2005
Active Learning of Model Evidence Using Bayesian Quadrature MA Osborne, D Duvenaud, R Garnett, CE Rasmussen, SJ Roberts, ... Advances in Neural Processing Systems 25, 46-54, 2013	71	2013
Adaptive regularization LK Hansen, CE Rasmussen, C Svarer, J Larsen Neural Networks for Signal Processing [1994] IV. Proceedings of the 1994 …, 1994	20	1994
Adaptive sequential Bayesian change point detection R Turner, Y Saatci, CE Rasmussen	34	2009
Adaptive, cautious, predictive control with Gaussian process priors R Murray-Smith, D Sbarbaro, CE Rasmussen, A Girard Elsevier Science, 2003	58	2003
Additive Gaussian Processes D Duvenaud, H Nickisch, CE Rasmussen Neural Information Processing Systems 24, 226-234, 2012	169	2012
Advances in Gaussian processes CE Rasmussen Advances in Neural Information Processing Systems, 2006	17	2006
Analysis of some methods for reduced rank Gaussian process regression J Quinonero-Candela, CE Rasmussen Switching and Learning in Feedback Systems, 98-127, 2005	25	2005
Approximate dynamic programming with Gaussian processes MP Deisenroth, J Peters, CE Rasmussen American Control Conference, 2008, 4480-4485, 2008	52	2008
Approximate inference for robust Gaussian process regression M Kuss, T Pfingsten, L Csató, CE Rasmussen Max Planck Inst. Biological Cybern., Tubingen, GermanyTech. Rep 136, 2005	20	2005
Approximation methods for Gaussian process regression J Quinonero-Candela, CE Rasmussen, CKI Williams Large-scale kernel machines, 203-224, 2007	120	2007
Approximations for binary Gaussian process classification H Nickisch, CE Rasmussen Journal of Machine Learning Research 9, 2035-2078, 2008	292	2008
Assessing approximate inference for binary Gaussian process classification M Kuss, CE Rasmussen The Journal of Machine Learning Research 6, 1679-1704, 2005	309	2005
Assessing Approximations for Gaussian Process Classiﬁcation M Kuss, CE Rasmussen Neural Information Processing Systems, 699-706, 2006	39*	2006

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