Yee Whye Teh - Google Scholar Citations

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	All	Since 2014
Citations	27426	20381
h-index	54	46
i10-index	122	111

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Max WellingProfessor Machine Learning, University of AmsterdamVerified email at uva.nl
Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleVerified email at cs.toronto.edu
Simon OsinderoDeepMindVerified email at google.com
Michael I. JordanProfessor of EECS and Professor of Statistics, University of California, BerkeleyVerified email at cs.berkeley.edu
Frank WoodUniversity of British ColumbiaVerified email at cs.ubc.ca
Chris J. MaddisonDPhil in Statistics, University of Oxford, DeepMindVerified email at cs.toronto.edu
Balaji LakshminarayananResearch Scientist at Google DeepMindVerified email at google.com
Andriy MnihResearch Scientist at DeepMindVerified email at cs.toronto.edu
Nicolas HeessDeepMindVerified email at google.com
Matthew J. BealChicago Trading CompanyVerified email at chicagotrading.com
Dilan GorurDeepMindVerified email at google.com
Daniel M. RoyAssistant Professor of Statistics, University of TorontoVerified email at utstat.toronto.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerified email at eng.cam.ac.uk
Razvan PascanuResearch Scientist at Google DeepMindVerified email at google.com
Tom RainforthUniversity of OxfordVerified email at stats.ox.ac.uk
David BleiProfessor of Statistics and Computer Science, Columbia UniversityVerified email at columbia.edu
Charles BlundellResearch Scientist at DeepMindVerified email at google.com
Vinayak RaoAssistant Professor, Department of Statistics, Purdue UniversityVerified email at purdue.edu
Jan GasthausGatsby Computational Neuroscience Unit, UCLVerified email at ucl.ac.uk
Jonathan SchwarzDeepMind, Gatsby Computational Neuroscience Unit - UCLVerified email at google.com

Yee Whye Teh

Professor of Statistical Machine Learning, Oxford, Research Scientist, DeepMind

Verified email at stats.ox.ac.uk - Homepage

Machine Learning Artificial Intelligence Statistics Computer Science


Title	Cited by	Year
A fast learning algorithm for deep belief nets GE Hinton, S Osindero, YW Teh Neural computation 18 (7), 1527-1554, 2006	11673	2006
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes. YW Teh, MI Jordan, MJ Beal, DM Blei NIPS, 2005	3929	2005
Bayesian Learning via Stochastic Gradient Langevin Dynamics M Welling, YW Teh ICML, 2011	788	2011
On smoothing and inference for topic models A Asuncion, M Welling, P Smyth, YW Teh arXiv preprint arXiv:1205.2662, 2009	598	2009
The concrete distribution: A continuous relaxation of discrete random variables CJ Maddison, A Mnih, YW Teh ICLR, 2017	597	2017
A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation YW Teh, D Newman, M Welling Advances in neural information processing systems, 1353-1360, 2007	590	2007
A hierarchical Bayesian language model based on Pitman-Yor processes YW Teh Proceedings of the 21st International Conference on Computational …, 2006	543	2006
Dirichlet process YW Teh Encyclopedia of machine learning, 280-287, 2010	465	2010
Names and faces in the news TL Berg, AC Berg, J Edwards, M Maire, R White, YW Teh, ... Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision …, 2004	462	2004
A fast and simple algorithm for training neural probabilistic language models A Mnih, YW Teh arXiv preprint arXiv:1206.6426, 2012	415	2012
Hierarchical Bayesian nonparametric models with applications YW Teh, MI Jordan Bayesian nonparametrics 1, 158-207, 2010	320	2010
Stick-breaking construction for the Indian buffet process YW Teh, D Grür, Z Ghahramani Artificial Intelligence and Statistics, 556-563, 2007	261	2007
Beam sampling for the infinite hidden Markov model J Van Gael, Y Saatci, YW Teh, Z Ghahramani Proceedings of the 25th international conference on Machine learning, 1088-1095, 2008	259	2008
Automatic alignment of local representations YW Teh, ST Roweis Advances in neural information processing systems, 865-872, 2003	257	2003
Semiparametric latent factor models M Seeger, YW Teh, M Jordan	209	2005
Variational Bayesian approach to movie rating prediction YJ Lim, YW Teh Proceedings of KDD cup and workshop 7, 15-21, 2007	202	2007
Collapsed Variational Dirichlet Process Mixture Models. K Kurihara, M Welling, YW Teh IJCAI 7, 2796-2801, 2007	194	2007
Bayesian nonparametric models P Orbanz, YW Teh Encyclopedia of Machine Learning, 81-89, 2010	185	2010
Collapsed variational inference for HDP YW Teh, K Kurihara, M Welling Advances in neural information processing systems, 1481-1488, 2008	179	2008
Stochastic gradient Riemannian Langevin dynamics on the probability simplex S Patterson, YW Teh Advances in neural information processing systems, 3102-3110, 2013	175	2013

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