Zoubin Ghahramani

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyEmail confirmado em cs.berkeley.edu
Yarin GalAssociate Professor, University of OxfordEmail confirmado em cs.ox.ac.uk
Daniel WolpertProfessor of Neuroscience, Columbia UniversityEmail confirmado em columbia.edu
Xiaojin ZhuProfessor in Computer Science at University of Wisconsin-MadisonEmail confirmado em cs.wisc.edu
Geoffrey HintonEmeritus Prof. Computer Science, University of TorontoEmail confirmado em cs.toronto.edu
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeEmail confirmado em cam.ac.uk
José Miguel Hernández-LobatoProfessor of Machine Learning, University of CambridgeEmail confirmado em cam.ac.uk
Matthew J. BealChicago Trading CompanyEmail confirmado em chicagotrading.com
Katherine HellerGoogle ResearchEmail confirmado em gatsby.ucl.ac.uk
David A. KnowlesColumbia University & New York Genome CenterEmail confirmado em columbia.edu
Alexander G. D. G. MatthewsDeepMindEmail confirmado em google.com
Tommi JaakkolaMITEmail confirmado em csail.mit.edu
Sam Roweis (Memorial)New York UniversityEmail confirmado em buffalo.edu
Wei Chu（褚崴）InfEmail confirmado em gatsby.ucl.ac.uk
Richard E TurnerProfessor, University of CambridgeEmail confirmado em cam.ac.uk
Neil HoulsbyGoogleEmail confirmado em google.com
Ryan P. AdamsPrinceton UniversityEmail confirmado em princeton.edu
James Robert LloydPhD from Machine Learning Group, Cambridge UniversityEmail confirmado em cam.ac.uk
Amar ShahPhD student, University of CambridgeEmail confirmado em cam.ac.uk
Naonori Ueda理化学研究所/NTTコミュニケーション科学基礎研究所 /Email confirmado em riken.jp

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Zoubin Ghahramani

Professor, University of Cambridge, and Distinguished Researcher, Google

Email confirmado em eng.cam.ac.uk - Página inicial

Machine Learning Bayesian Statistics Neural Networks Artificial Intelligence


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Dropout as a bayesian approximation: Representing model uncertainty in deep learning Y Gal, Z Ghahramani international conference on machine learning, 1050-1059, 2016	11485	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	5825*	2003
An introduction to variational methods for graphical models MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul Machine learning 37, 183-233, 1999	5575	1999
An internal model for sensorimotor integration DM Wolpert, Z Ghahramani, MI Jordan Science 269 (5232), 1880-1882, 1995	4331	1995
Active learning with statistical models DA Cohn, Z Ghahramani, MI Jordan Journal of Artificial Intelligence Research 4, 129--145, 1996	2597	1996
Computational principles of movement neuroscience DM Wolpert, Z Ghahramani Nature Neuroscience 3, 1212-1217, 2000	2520	2000
Probabilistic machine learning and artificial intelligence Z Ghahramani Nature 521 (7553), 452-459, 2015	2404	2015
Sparse Gaussian processes using pseudo-inputs E Snelson, Z Ghahramani Advances in Neural Information Processing Systems 18, 1257--1264, 2006	2344	2006
Learning from labeled and unlabeled data with label propagation X ZhuЃ, Z GhahramaniЃн ProQuest number: information to all users, 2002	2112	2002
A theoretically grounded application of dropout in recurrent neural networks Y Gal, Z Ghahramani Advances in neural information processing systems 29, 2016	2093	2016
Deep bayesian active learning with image data Y Gal, R Islam, Z Ghahramani International conference on machine learning, 1183-1192, 2017	2079	2017
Factorial hidden Markov models Z Ghahramani, M Jordan Advances in neural information processing systems 8, 1995	1906	1995
A unifying review of linear Gaussian models S Roweis, Z Ghahramani Neural computation 11 (2), 305-345, 1999	1346	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	1332	2010
An introduction to hidden Markov models and Bayesian networks Z Ghahramani International journal of pattern recognition and artificial intelligence 15 …, 2001	1302	2001
Unsupervised learning Z Ghahramani Summer school on machine learning, 72-112, 2003	1241	2003
Perspectives and problems in motor learning DM Wolpert, Z Ghahramani, JR Flanagan Trends in cognitive sciences 5 (11), 487-494, 2001	1102	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	1084	2004
The EM algorithm for mixtures of factor analyzers Z Ghahramani, GE Hinton Technical Report CRG-TR-96-1, University of Toronto, 1996	1013	1996
Bayesian convolutional neural networks with Bernoulli approximate variational inference Y Gal, Z Ghahramani arXiv preprint arXiv:1506.02158, 2015	981	2015

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