Carl Edward Rasmussen 个人学术档案

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引用	52971	29819
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Chris WilliamsProfessor of Machine Learning, University of Edinburgh在 inf.ed.ac.uk 的电子邮件经过验证
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, Google在 eng.cam.ac.uk 的电子邮件经过验证
Marc DeisenrothUniversity College London在 ucl.ac.uk 的电子邮件经过验证
Joaquin Quiñonero CandelaAI Technical Fellow at LinkedIn在 linkedin.com 的电子邮件经过验证
Roderick Murray-SmithProfessor of Computing Science, University of Glasgow, School of Computing Science在 glasgow.ac.uk 的电子邮件经过验证
Hannes NickischPhilips Research在 philips.com 的电子邮件经过验证
Jan PetersProfessor for Intelligent Autonomous Systems at Technische Universität Darmstadt在 ias.tu-darmstadt.de 的电子邮件经过验证
Dilan GorurDeepMind在 google.com 的电子邮件经过验证
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich在 tuebingen.mpg.de 的电子邮件经过验证
Lars Kai HansenProfessor, Cognitive Systems, DTU Compute, Technical University of Denmark在 dtu.dk 的电子邮件经过验证
Roger FrigolaMachine Learning at www.rogerfrigola.com在 rogerfrigola.com 的电子邮件经过验证
Gunnar RätschProfessor, ETH Zürich在 inf.ethz.ch 的电子邮件经过验证
Fabian SinzProfessor for Machine Learning, University Göttingen在 cs.uni-goettingen.de 的电子邮件经过验证
Miguel Lázaro-GredillaVP of research, Vicarious AI在 vicarious.com 的电子邮件经过验证
Robert C. WilliamsonUniversity of Tübingen在 uni-tuebingen.de 的电子邮件经过验证
Samy BengioSenior Director, AI and Machine Learning Research, Apple在 apple.com 的电子邮件经过验证
Cheng Soon OngData61, CSIRO, Canberra在 anu.edu.au 的电子邮件经过验证
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, Google在 cs.toronto.edu 的电子邮件经过验证
Volker TrespLudwig Maximilian University of Munich / München (LMU) and Siemens AG在 dbs.ifi.lmu.de 的电子邮件经过验证

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Carl Edward Rasmussen

Professor of Machine Learning, University of Cambridge

在 cam.ac.uk 的电子邮件经过验证 - 首页

Gaussian processes Bayesian inference machine learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Gaussian Processes for Machine Learning CE Rasmussen, CKI Williams the MIT Press, 2006	26059	2006
Gaussian processes in machine learning CE Rasmussen Lecture notes in computer science 3176, 63-71, 2004	3696	2004
The infinite hidden Markov model MJ Beal, Z Ghahramani, CE Rasmussen Advances in neural information processing systems 14, 577-584, 2002	2583*	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	2202	2005
The infinite Gaussian mixture model CE Rasmussen Advances in neural information processing systems 12, 554-560, 2000	1670	2000
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	1665	2011
Gaussian processes for regression CKI Williams, CE Rasmussen Advances in Neural Processing Systems 8, 514 - 520, 1996	1562	1996
Gaussian processes for machine learning (GPML) toolbox CE Rasmussen, H Nickisch The Journal of Machine Learning Research 11, 3011-3015, 2010	1097	2010
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	696	2015
Evaluation of Gaussian processes and other methods for non-linear regression CE Rasmussen University of Toronto, 1996	645	1996
Infinite mixtures of Gaussian process experts CE Rasmussen, Z Ghahramani Advances in neural information processing systems 14 2, 881-888, 2002	613	2002
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	589*	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	520*	2002
Sparse spectrum Gaussian process regression M Lázaro-Gredilla, J Quiñonero-Candela, CE Rasmussen, ... The Journal of Machine Learning Research 11, 1865-1881, 2010	506	2010
Approximations for binary Gaussian process classification H Nickisch, CE Rasmussen Journal of Machine Learning Research 9, 2035-2078, 2008	438	2008
Warped Gaussian processes E Snelson, CE Rasmussen, Z Ghahramani Advances in neural information processing systems 16, 337-344, 2004	412	2004
Assessing approximate inference for binary Gaussian process classification M Kuss, CE Rasmussen The Journal of Machine Learning Research 6, 1679-1704, 2005	389	2005
Derivative observations in Gaussian process models of dynamic systems E Solak, R Murray-Smith, WE Leithead, DJ Leith, CE Rasmussen MIT Press, 2003	371	2003
Occam's razor CE Rasmussen, Z Ghahramani Advances in neural information processing systems, 294-300, 2001	356	2001
Bayesian monte Carlo CE Rasmussen, Z Ghahramani Advances in neural information processing systems 15, 489-496, 2003	342*	2003

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