Yee Whye Teh

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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 OsinderoSenior Staff Scientist @ DeepMindVerified email at google.com
Razvan PascanuResearch Scientist at Google DeepMindVerified email at google.com
Nicolas HeessDeepMindVerified email at google.com
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Chris J. MaddisonUniversity of TorontoVerified email at cs.toronto.edu
Tom RainforthUniversity of OxfordVerified email at stats.ox.ac.uk
Balaji LakshminarayananStaff Research Scientist at Google BrainVerified email at google.com
Frank WoodUniversity of British ColumbiaVerified email at cs.ubc.ca
Jonathan Richard SchwarzDeepMind, University College LondonVerified email at google.com
Andriy MnihResearch Scientist at DeepMindVerified email at cs.toronto.edu
Arnaud DoucetProfessor of Statistics, University of Oxford & Research Scientist, Google DeepMindVerified email at stats.ox.ac.uk
Stefano FavaroUniversity of Torino and Collegio Carlo AlbertoVerified email at unito.it
Adam R. KosiorekResearch Scientist, DeepMindVerified email at google.com
Yarin GalAssociate Professor, University of OxfordVerified email at cs.ox.ac.uk
Dilan GorurDeepMindVerified email at google.com
Wojciech Marian CzarneckiIsomorphic LabsVerified email at google.com
Daniel M. RoyUniversity of Toronto, Dept of Statistical Sciences; Computer ScienceVerified email at utoronto.ca
Leonard HasencleverResearch 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	17540	2006
Hierarchical Dirichlet Processes YW Teh, MI Jordan, MJ Beal, DM Blei Journal of the American Statistical Association 101, 1566-1581, 2006	4272	2006
Bayesian Learning via Stochastic Gradient Langevin Dynamics M Welling, YW Teh ICML, 2011	1717	2011
The concrete distribution: A continuous relaxation of discrete random variables CJ Maddison, A Mnih, YW Teh ICLR, 2017	1678	2017
On smoothing and inference for topic models A Asuncion, M Welling, P Smyth, YW Teh arXiv preprint arXiv:1205.2662, 2009	759	2009
A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation Y Teh, D Newman, M Welling Advances in neural information processing systems 19, 2006	738	2006
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes. YW Teh, MI Jordan, MJ Beal, DM Blei NIPS, 2005	663	2005
A hierarchical Bayesian language model based on Pitman-Yor processes YW Teh Proceedings of the 21st International Conference on Computational …, 2006	659	2006
A fast and simple algorithm for training neural probabilistic language models A Mnih, YW Teh arXiv preprint arXiv:1206.6426, 2012	616	2012
Dirichlet Process. YW Teh Encyclopedia of machine learning 1063, 280-287, 2010	607	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	527	2004
Inferring the effectiveness of government interventions against COVID-19 JM Brauner, S Mindermann, M Sharma, D Johnston, J Salvatier, ... Science 371 (6531), eabd9338, 2021	520	2021
Set transformer J Lee, Y Lee, J Kim, AR Kosiorek, S Choi, YW Teh International Conference on Machine Learning 2019. arXiv:1810.00825, 2018	433*	2018
Progress & Compress: A scalable framework for continual learning J Schwarz, J Luketina, WM Czarnecki, A Grabska-Barwinska, YW Teh, ... ICML2018 arXiv:1805.06370, 2018	422	2018
Hierarchical Bayesian nonparametric models with applications YW Teh, MI Jordan Bayesian nonparametrics 1, 158-207, 2010	408	2010
Do Deep Generative Models Know What They Don't Know? E Nalisnick, A Matsukawa, YW Teh, D Gorur, B Lakshminarayanan ICLR2019, 2018	388	2018
Distral: Robust multitask reinforcement learning YW Teh, V Bapst, WM Czarnecki, J Quan, J Kirkpatrick, R Hadsell, ... NIPS2017, 2017	382	2017
Conditional Neural Processes M Garnelo, D Rosenbaum, CJ Maddison, T Ramalho, D Saxton, ... ICML2018 arXiv:1807.01613, 2018	358	2018
Stick-breaking construction for the Indian buffet process YW Teh, D Grür, Z Ghahramani Artificial Intelligence and Statistics, 556-563, 2007	323	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	319	2008

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