Yee Whye Teh - Google Scholar Citations

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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
Balaji LakshminarayananResearch Scientist at Google DeepMindVerified email at google.com
Chris J. MaddisonDPhil in Statistics, University of Oxford, DeepMindVerified email at stats.ox.ac.uk
Andriy MnihResearch Scientist at DeepMindVerified email at cs.toronto.edu
Matthew J. BealChicago Trading CompanyVerified email at chicagotrading.com
Nicolas HeessDeepMindVerified email at google.com
Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerified email at eng.cam.ac.uk
Dilan GorurDeepMindVerified email at google.com
Daniel M. RoyAssistant Professor of Statistics, University of TorontoVerified email at utstat.toronto.edu
David BleiProfessor of Statistics and Computer Science, Columbia UniversityVerified email at columbia.edu
Razvan PascanuStaff Research Scientist at Google DeepMindVerified email at google.com
Jan GasthausGatsby Computational Neuroscience Unit, UCLVerified email at ucl.ac.uk
Charles BlundellResearch Scientist at DeepMindVerified email at google.com
Vinayak RaoAssistant Professor, Department of Statistics, Purdue UniversityVerified email at purdue.edu
Tom RainforthUniversity of OxfordVerified email at stats.ox.ac.uk
David ForsythProfessor of Computer Science, University of Illinois, Urbana ChampaignVerified email at uiuc.edu

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	11032	2006
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes. YW Teh, MI Jordan, MJ Beal, DM Blei NIPS, 2005	3826	2005
Hierarchical Dirichlet Processes YW Teh, MI Jordan, MJ Beal, DM Blei Journal of the American Statistical Association 101, 1566-1581, 2006	3824*	2006
Bayesian Learning via Stochastic Gradient Langevin Dynamics M Welling, YW Teh ICML, 2011	720	2011
On smoothing and inference for topic models A Asuncion, M Welling, P Smyth, YW Teh arXiv preprint arXiv:1205.2662, 2009	575	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	564	2007
A hierarchical Bayesian language model based on Pitman-Yor processes YW Teh Proceedings of the 21st International Conference on Computational …, 2006	530	2006
The concrete distribution: A continuous relaxation of discrete random variables CJ Maddison, A Mnih, YW Teh NIPS, 2016	493	2016
Dirichlet process YW Teh Encyclopedia of machine learning, 280-287, 2010	451	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	438	2004
A fast and simple algorithm for training neural probabilistic language models A Mnih, YW Teh arXiv preprint arXiv:1206.6426, 2012	390	2012
Hierarchical Bayesian nonparametric models with applications YW Teh, MI Jordan Bayesian nonparametrics 1, 158-207, 2010	313	2010
Automatic alignment of local representations YW Teh, ST Roweis Advances in neural information processing systems, 865-872, 2003	257	2003
Stick-breaking construction for the Indian buffet process YW Teh, D Grür, Z Ghahramani Artificial Intelligence and Statistics, 556-563, 2007	255	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	253	2008
Semiparametric latent factor models M Seeger, YW Teh, M Jordan	201	2005
Variational Bayesian approach to movie rating prediction YJ Lim, YW Teh Proceedings of KDD cup and workshop 7, 15-21, 2007	198	2007
Collapsed Variational Dirichlet Process Mixture Models. K Kurihara, M Welling, YW Teh IJCAI 7, 2796-2801, 2007	189	2007
Collapsed variational inference for HDP YW Teh, K Kurihara, M Welling Advances in neural information processing systems, 1481-1488, 2008	177	2008
Bayesian nonparametric models P Orbanz, YW Teh Encyclopedia of Machine Learning, 81-89, 2010	176	2010

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