Yee Whye Teh - Google Scholar Citations

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Citations	31387	21953
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Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleVerified email at cs.toronto.edu
Max WellingProfessor Machine Learning, University of AmsterdamVerified email at uva.nl
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 LakshminarayananStaff Research Scientist at Google BrainVerified email at google.com
Nicolas HeessDeepMindVerified email at google.com
Razvan PascanuResearch Scientist at Google DeepMindVerified email at google.com
Andriy MnihResearch Scientist at DeepMindVerified email at cs.toronto.edu
Stefano FavaroUniversity of Torino and Collegio Carlo AlbertoVerified email at unito.it
Tom RainforthUniversity of OxfordVerified email at stats.ox.ac.uk
Daniel M. RoyUniversity of Toronto, Dept of Statistical Sciences; Computer ScienceVerified email at utstat.toronto.edu
Dilan GorurDeepMindVerified email at google.com
Matthew J. BealChicago Trading CompanyVerified email at chicagotrading.com
Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerified email at eng.cam.ac.uk
David BleiProfessor of Statistics and Computer Science, Columbia UniversityVerified email at columbia.edu
Jonathan SchwarzDeepMind, Gatsby Computational Neuroscience Unit - UCLVerified email at google.com
Adam R. KosiorekPhD in Information Engineering, University of OxfordVerified email at robots.ox.ac.uk
Charles BlundellResearch Scientist at DeepMindVerified 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 Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A fast learning algorithm for deep belief nets GE Hinton, S Osindero, YW Teh Neural computation 18 (7), 1527-1554, 2006	13313	2006
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes. YW Teh, MI Jordan, MJ Beal, DM Blei NIPS, 2005	4202	2005
Hierarchical Dirichlet Processes YW Teh, MI Jordan, MJ Beal, DM Blei Journal of the American Statistical Association 101, 1566-1581, 2006	4200*	2006
Bayesian Learning via Stochastic Gradient Langevin Dynamics M Welling, YW Teh ICML, 2011	991	2011
The concrete distribution: A continuous relaxation of discrete random variables CJ Maddison, A Mnih, YW Teh ICLR, 2017	856	2017
On smoothing and inference for topic models A Asuncion, M Welling, P Smyth, YW Teh arXiv preprint arXiv:1205.2662, 2009	650	2009
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	650	2007
A hierarchical Bayesian language model based on Pitman-Yor processes YW Teh Proceedings of the 21st International Conference on Computational …, 2006	586	2006
Dirichlet Process. YW Teh Encyclopedia of machine learning, 280-287, 2010	514	2010
A fast and simple algorithm for training neural probabilistic language models A Mnih, YW Teh arXiv preprint arXiv:1206.6426, 2012	479	2012
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	471	2004
Hierarchical Bayesian nonparametric models with applications YW Teh, MI Jordan Bayesian nonparametrics 1, 158-207, 2010	344	2010
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	285	2008
Stick-breaking construction for the Indian buffet process YW Teh, D Grür, Z Ghahramani Artificial Intelligence and Statistics, 556-563, 2007	280	2007
Automatic alignment of local representations YW Teh, ST Roweis Advances in neural information processing systems, 865-872, 2003	264	2003
Semiparametric latent factor models M Seeger, YW Teh, M Jordan	224	2005
Collapsed Variational Dirichlet Process Mixture Models. K Kurihara, M Welling, YW Teh IJCAI 7, 2796-2801, 2007	212	2007
Variational Bayesian approach to movie rating prediction YJ Lim, YW Teh Proceedings of KDD cup and workshop 7, 15-21, 2007	205	2007
Bayesian Nonparametric Models. P Orbanz, YW Teh Encyclopedia of machine learning, 2010	204	2010
Stochastic gradient Riemannian Langevin dynamics on the probability simplex S Patterson, YW Teh Advances in neural information processing systems, 3102-3110, 2013	192	2013

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