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 WangHead of AML Research at ByteDanceVerified email at cs.princeton.edu
Matthew D. HoffmanResearch Scientist, Google ResearchVerified email at google.com
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-GraberAssociate Professor, University of MarylandVerified email at umiacs.umd.edu
Prem GopalanSenior Technical Manager, The Voleon GroupVerified email at cs.princeton.edu
Jonathan ChangFacebookVerified email at fb.com
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
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindVerified email at stats.ox.ac.uk
Allison J.B. ChaneyDuke UniversityVerified email at duke.edu
David MimnoAssociate Professor, Cornell UniversityVerified email at cornell.edu
Joshua B. TenenbaumMITVerified email at mit.edu
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
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
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	43000	2003
Probabilistic topic models DM Blei Communications of the ACM 55 (4), 77-84, 2012	5833	2012
Hierarchical dirichlet processes YW Teh, MI Jordan, MJ Beal, DM Blei Journal of the american statistical association 101 (476), 1566-1581, 2006	4821*	2006
Topic models DM Blei, JD Laﬀerty Text mining, 101-124, 2009	4153	2009
Variational inference: A review for statisticians DM Blei, A Kucukelbir, JD McAuliffe Journal of the American statistical Association 112 (518), 859-877, 2017	3046	2017
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	2522	2009
Stochastic variational inference MD Hoffman, DM Blei, C Wang, J Paisley Journal of Machine Learning Research, 2013	2310	2013
Mixed membership stochastic blockmodels EM Airoldi, D Blei, S Fienberg, E Xing Advances in neural information processing systems 21, 2008	2301	2008
Matching words and pictures K Barnard, P Duygulu, D Forsyth, N De Freitas, DM Blei, MI Jordan Test accounts, 2003	2066	2003
Supervised topic models J Mcauliffe, D Blei Advances in neural information processing systems 20, 2007	2024	2007
Online learning for latent dirichlet allocation M Hoffman, F Bach, D Blei advances in neural information processing systems 23, 2010	1890	2010
A correlated topic model of science DM Blei, JD Lafferty The annals of applied statistics 1 (1), 17-35, 2007	1830*	2007
Collaborative topic modeling for recommending scientific articles C Wang, DM Blei Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011	1821	2011
Variational inference for Dirichlet process mixtures DM Blei, MI Jordan Bayesian analysis 1 (1), 121-143, 2006	1612	2006
Modeling annotated data DM Blei, MI Jordan Proceedings of the 26th annual international ACM SIGIR conference on …, 2003	1491	2003
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	1352	2003
Correlated topic models D Blei, J Lafferty Advances in neural information processing systems 18, 147, 2006	1129	2006
Black box variational inference R Ranganath, S Gerrish, D Blei Artificial intelligence and statistics, 814-822, 2014	954	2014
Relational topic models for document networks J Chang, D Blei Artificial intelligence and statistics, 81-88, 2009	927*	2009
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies DM Blei, TL Griffiths, MI Jordan Journal of the ACM (JACM) 57 (2), 1-30, 2010	809	2010

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