David Blei

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Chong WangAppleVerified email at cs.princeton.edu
John PaisleyColumbia UniversityVerified email at columbia.edu
Edoardo M AiroldiProfessor of Statistics & Data Science Temple University & PI, Harvard UniversityVerified email at fas.harvard.edu
Jordan Boyd-GraberFull Professor, University of MarylandVerified email at umiacs.umd.edu
Jonathan ChangFacebookVerified email at fb.com
Prem GopalanCTO, The Voleon GroupVerified email at cs.princeton.edu
Samuel GershmanProfessor, Harvard UniversityVerified email at fas.harvard.edu
Jon McAuliffeProfessor (Adj.) of Statistics, University of California, BerkeleyVerified email at stat.berkeley.edu
Thomas L. GriffithsProfessor of Psychology and Computer Science, Princeton UniversityVerified email at princeton.edu
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
Joshua B. TenenbaumMITVerified email at mit.edu
Allison J.B. ChaneyDuke UniversityVerified email at duke.edu
David MimnoAssociate Professor, Cornell UniversityVerified email at cornell.edu
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
Kenneth A. NormanProfessor of Psychology and Neuroscience, Princeton UniversityVerified email at princeton.edu
Peter I FrazierAssociate Professor of Operations Research and Information Engineering, Cornell UniversityVerified email at cornell.edu
Mingyuan ZhouAssociate Professor, University of Texas at AustinVerified email at mccombs.utexas.edu
Pinar Duygulu SahinProf. , Department of Computer Engineering, Hacettepe University, Ankara, TurkeyVerified email at cs.hacettepe.edu.tr
David ForsythProfessor of Computer Science, University of Illinois, Urbana ChampaignVerified email at uiuc.edu

David Blei

Professor of Statistics and Computer Science, Columbia University

Verified email at columbia.edu - Homepage

Machine Learning Statistics Probabilistic topic models Bayesian nonparametrics Approximate posterior inference


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Latent dirichlet allocation DM Blei, AY Ng, MI Jordan Journal of machine Learning research 3 (Jan), 993-1022, 2003	57327	2003
Probabilistic topic models DM Blei Communications of the ACM 55 (4), 77-84, 2012	8368	2012
Variational inference: A review for statisticians DM Blei, A Kucukelbir, JD McAuliffe Journal of the American statistical Association 112 (518), 859-877, 2017	6391	2017
Sharing clusters among related groups: Hierarchical Dirichlet processes Y Teh, M Jordan, M Beal, D Blei Advances in neural information processing systems 17, 2004	5530	2004
Dynamic topic models DM Blei, JD Lafferty Proceedings of the 23rd international conference on Machine learning, 113-120, 2006	5432*	2006
Reading tea leaves: How humans interpret topic models J Chang, S Gerrish, C Wang, J Boyd-Graber, D Blei Advances in neural information processing systems 22, 2009	3560	2009
Stochastic variational inference MD Hoffman, DM Blei, C Wang, J Paisley the Journal of machine Learning research 14 (1), 1303-1347, 2013	3305	2013
Mixed membership stochastic blockmodels EM Airoldi, D Blei, S Fienberg, E Xing Advances in neural information processing systems 21, 2008	2717	2008
A correlated topic model of science DM Blei, JD Lafferty The annals of applied statistics, 17-35, 2007	2478*	2007
Online learning for latent dirichlet allocation M Hoffman, F Bach, D Blei advances in neural information processing systems 23, 2010	2349	2010
Supervised topic models J Mcauliffe, D Blei Advances in neural information processing systems 20, 2007	2348	2007
Collaborative topic modeling for recommending scientific articles C Wang, DM Blei Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011	2136	2011
Matching words and pictures K Barnard, P Duygulu, D Forsyth, N Freitas, DM Blei, MI Jordan Journal of machine learning research 3 (Feb), 1107-1135, 2003	2113	2003
Variational inference for Dirichlet process mixtures DM Blei, MI Jordan	1981	2006
Hierarchical topic models and the nested Chinese restaurant process T Griffiths, M Jordan, J Tenenbaum, D Blei Advances in neural information processing systems 16, 2003	1594	2003
Modeling annotated data DM Blei, MI Jordan Proceedings of the 26th annual international ACM SIGIR conference on …, 2003	1591	2003
Black box variational inference R Ranganath, S Gerrish, D Blei Artificial intelligence and statistics, 814-822, 2014	1473	2014
Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of US government arts funding P DiMaggio, M Nag, D Blei Poetics 41 (6), 570-606, 2013	1468	2013
Correlated topic models D Blei, J Lafferty Advances in neural information processing systems 18, 147, 2006	1446	2006
Relational topic models for document networks J Chang, D Blei Artificial intelligence and statistics, 81-88, 2009	1058*	2009

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