Zoubin Ghahramani

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyEmail verificata su cs.berkeley.edu
Daniel WolpertProfessor of Neuroscience, Columbia UniversityEmail verificata su columbia.edu
Xiaojin ZhuProfessor in Computer Science at University of Wisconsin-MadisonEmail verificata su cs.wisc.edu
Yarin GalAssociate Professor, University of OxfordEmail verificata su cs.ox.ac.uk
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoEmail verificata su cs.toronto.edu
Katherine HellerGoogle ResearchEmail verificata su gatsby.ucl.ac.uk
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeEmail verificata su cam.ac.uk
José Miguel Hernández-LobatoProfessor of Machine Learning, University of CambridgeEmail verificata su cam.ac.uk
Matthew J. BealChicago Trading CompanyEmail verificata su chicagotrading.com
Alexander G. D. G. MatthewsDeepMindEmail verificata su google.com
Sam Roweis (Memorial)New York UniversityEmail verificata su buffalo.edu
David A. KnowlesColumbia University & New York Genome CenterEmail verificata su columbia.edu
Tommi JaakkolaMITEmail verificata su csail.mit.edu
Richard E TurnerProfessor, University of CambridgeEmail verificata su cam.ac.uk
Wei Chu（褚崴）InfEmail verificata su gatsby.ucl.ac.uk
Neil HoulsbyGoogleEmail verificata su google.com
Lawrence K SaulSenior Research Scientist, Center for Computational Mathematics, Flatiron InstituteEmail verificata su flatironinstitute.org
James HensmanMicrosoft ResearchEmail verificata su microsoft.com
Ryan P. AdamsPrinceton UniversityEmail verificata su princeton.edu
Hugh Durrant-WhyteUniversity of SydneyEmail verificata su sydney.edu.au

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Zoubin Ghahramani

Professor, University of Cambridge, and Distinguished Researcher, Google

Email verificata su eng.cam.ac.uk - Home page

Machine Learning Bayesian Statistics Neural Networks Artificial Intelligence


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Dropout as a bayesian approximation: Representing model uncertainty in deep learning Y Gal, Z Ghahramani international conference on machine learning, 1050-1059, 2016	8823	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	5518*	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	4084	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	2395	2000
Sparse Gaussian processes using pseudo-inputs E Snelson, Z Ghahramani Advances in Neural Information Processing Systems 18, 1257--1264, 2006	2159	2006
Probabilistic machine learning and artificial intelligence Z Ghahramani Nature 521 (7553), 452-459, 2015	1980	2015
Learning from labeled and unlabeled data with label propagation X ZhuЃ, Z GhahramaniЃн ProQuest Number: INFORMATION TO ALL USERS, 2002	1908	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	1845	1995
Deep bayesian active learning with image data Y Gal, R Islam, Z Ghahramani International conference on machine learning, 1183-1192, 2017	1589	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	1261	2010
An introduction to hidden Markov models and Bayesian networks Z Ghahramani International journal of pattern recognition and artificial intelligence 15 …, 2001	1226	2001
Perspectives and problems in motor learning DM Wolpert, Z Ghahramani, JR Flanagan Trends in cognitive sciences 5 (11), 487-494, 2001	1065	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	1013	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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