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. Computer Science, University of TorontoVerified email at cs.toronto.edu
Katherine HellerGoogle ResearchVerified email at gatsby.ucl.ac.uk
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
José Miguel Hernández-LobatoProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
Matthew J. BealChicago Trading CompanyVerified email at chicagotrading.com
Alexander G. D. G. MatthewsDeepMindVerified email at google.com
Sam Roweis (Memorial)New York UniversityVerified email at buffalo.edu
David A. KnowlesColumbia University & New York Genome CenterVerified email at columbia.edu
Tommi JaakkolaMITVerified email at csail.mit.edu
Richard E TurnerProfessor, University of CambridgeVerified email at cam.ac.uk
Wei Chu（褚崴）InfVerified 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
James HensmanMicrosoft ResearchVerified email at microsoft.com
Ryan P. AdamsPrinceton UniversityVerified email at princeton.edu
Hugh Durrant-WhyteUniversity of SydneyVerified email at sydney.edu.au

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	8838	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	5520*	2003
An introduction to variational methods for graphical models MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul Machine learning 37, 183-233, 1999	5173	1999
An internal model for sensorimotor integration DM Wolpert, Z Ghahramani, MI Jordan Science 269 (5232), 1880-1882, 1995	4089	1995
Active learning with statistical models DA Cohn, Z Ghahramani, MI Jordan Journal of Artificial Intelligence Research 4, 129--145, 1996	2414	1996
Computational principles of movement neuroscience DM Wolpert, Z Ghahramani Nature Neuroscience 3, 1212-1217, 2000	2396	2000
Sparse Gaussian processes using pseudo-inputs E Snelson, Z Ghahramani Advances in Neural Information Processing Systems 18, 1257--1264, 2006	2161	2006
Probabilistic machine learning and artificial intelligence Z Ghahramani Nature 521 (7553), 452-459, 2015	1989	2015
Learning from labeled and unlabeled data with label propagation X ZhuЃ, Z GhahramaniЃн ProQuest Number: INFORMATION TO ALL USERS, 2002	1909	2002
A theoretically grounded application of dropout in recurrent neural networks Y Gal, Z Ghahramani Advances in neural information processing systems 29, 2016	1879	2016
Factorial hidden Markov models Z Ghahramani, M Jordan Advances in neural information processing systems 8, 1995	1846	1995
Deep bayesian active learning with image data Y Gal, R Islam, Z Ghahramani International conference on machine learning, 1183-1192, 2017	1593	2017
A unifying review of linear Gaussian models S Roweis, Z Ghahramani Neural computation 11 (2), 305-345, 1999	1317	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	1262	2010
An introduction to hidden Markov models and Bayesian networks Z Ghahramani International journal of pattern recognition and artificial intelligence 15 …, 2001	1227	2001
Perspectives and problems in motor learning DM Wolpert, Z Ghahramani, JR Flanagan Trends in cognitive sciences 5 (11), 487-494, 2001	1066	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	1062	2004
Unsupervised learning Z Ghahramani Summer school on machine learning, 72-112, 2003	1016	2003
The EM algorithm for mixtures of factor analyzers Z Ghahramani, GE Hinton Technical Report CRG-TR-96-1, University of Toronto, 1996	974	1996
Infinite latent feature models and the Indian buffet process T Griffiths, Z Ghahramani Advances in Neural Information Processing Systems 18, 475--482, 2006	952*	2006

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