Zoubin Ghahramani

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Daniel WolpertProfessor of Neuroscience, Columbia UniversityVerified email at columbia.edu
Xiaojin ZhuProfessor in Computer Science at University of Wisconsin-MadisonVerified email at cs.wisc.edu
Yarin GalAssociate Professor, University of OxfordVerified email at cs.ox.ac.uk
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleVerified email at cs.toronto.edu
José Miguel Hernández-LobatoProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
Katherine HellerGoogle ResearchVerified email at gatsby.ucl.ac.uk
Matthew J. BealChicago Trading CompanyVerified email at chicagotrading.com
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
Alexander G. D. G. MatthewsDeepMindVerified email at google.com
David A. KnowlesColumbia University & New York Genome CenterVerified email at columbia.edu
Sam Roweis (Memorial)New York UniversityVerified email at buffalo.edu
Tommi JaakkolaMITVerified email at csail.mit.edu
Richard E TurnerProfessor, University of CambridgeVerified email at cam.ac.uk
Wei Chu（褚崴）AlibabaVerified email at gatsby.ucl.ac.uk
Neil HoulsbyGoogleVerified email at google.com
Lawrence K SaulSenior Research Scientist, Center for Computational Mathematics, Flatiron InstituteVerified email at flatironinstitute.org
Hugh Durrant-WhyteUniversity of SydneyVerified email at sydney.edu.au
Ryan P. AdamsPrinceton UniversityVerified email at princeton.edu
James HensmanMicrosoft ResearchVerified email at microsoft.com

Zoubin Ghahramani

Professor, University of Cambridge, and Distinguished Researcher, Google

Verified email at eng.cam.ac.uk - Homepage

Machine Learning Bayesian Statistics Neural Networks Artificial Intelligence


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Dropout as a bayesian approximation: Representing model uncertainty in deep learning Y Gal, Z Ghahramani international conference on machine learning, 1050-1059, 2016	7552	2016
Semi-supervised learning using Gaussian fields and harmonic functions X Zhu, Z Ghahramani, J Lafferty Proceedings of the Twentieth International Conference on Machine Learning …, 2003	5353*	2003
An introduction to variational methods for graphical models MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul Machine learning 37, 183-233, 1999	4976	1999
An internal model for sensorimotor integration DM Wolpert, Z Ghahramani, MI Jordan Science 269 (5232), 1880-1882, 1995	3932	1995
Computational principles of movement neuroscience DM Wolpert, Z Ghahramani Nature Neuroscience 3, 1212-1217, 2000	2309	2000
Active learning with statistical models DA Cohn, Z Ghahramani, MI Jordan Journal of Artificial Intelligence Research 4, 129--145, 1996	2305	1996
Sparse Gaussian processes using pseudo-inputs E Snelson, Z Ghahramani Advances in Neural Information Processing Systems 18, 1257--1264, 2006	2037	2006
Factorial hidden Markov models Z Ghahramani, M Jordan Advances in Neural Information Processing Systems 8, 1995	1817	1995
Learning from labeled and unlabeled data with label propagation X ZhuЃ, Z GhahramaniЃн	1813	2002
A theoretically grounded application of dropout in recurrent neural networks Y Gal, Z Ghahramani Advances in neural information processing systems 29, 2016	1778	2016
Probabilistic machine learning and artificial intelligence Z Ghahramani Nature 521 (7553), 452-459, 2015	1776	2015
Deep bayesian active learning with image data Y Gal, R Islam, Z Ghahramani International conference on machine learning, 1183-1192, 2017	1366	2017
A unifying review of linear Gaussian models S Roweis, Z Ghahramani Neural computation 11 (2), 305-345, 1999	1288	1999
Kronecker graphs: an approach to modeling networks. J Leskovec, D Chakrabarti, J Kleinberg, C Faloutsos, Z Ghahramani Journal of Machine Learning Research 11 (2), 2010	1221	2010
An introduction to hidden Markov models and Bayesian networks Z Ghahramani International journal of pattern recognition and artificial intelligence 15 …, 2001	1185	2001
Perspectives and problems in motor learning DM Wolpert, Z Ghahramani, JR Flanagan Trends in cognitive sciences 5 (11), 487-494, 2001	1048	2001
Simultaneous localization and mapping with sparse extended information filters S Thrun, Y Liu, D Koller, AY Ng, Z Ghahramani, H Durrant-Whyte The international journal of robotics research 23 (7-8), 693-716, 2004	1046	2004
The EM algorithm for mixtures of factor analyzers Z Ghahramani, GE Hinton Technical Report CRG-TR-96-1, University of Toronto, 1996	948	1996
Infinite latent feature models and the Indian buffet process T Griffiths, Z Ghahramani Advances in Neural Information Processing Systems 18, 475--482, 2006	936*	2006
Unsupervised learning Z Ghahramani Advanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra …, 2004	898	2004

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