Jon McAuliffe

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
David BleiProfessor of Statistics and Computer Science, Columbia UniversityVerified email at columbia.edu
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Alp KucukelbirAdjunct Professor of Computer Science, Columbia UniversityVerified email at cs.columbia.edu
Jeffrey RegierAssistant Professor, Department of Statistics, University of MichiganVerified email at umich.edu
Lior PachterBren Professor of Computational Biology, CaltechVerified email at caltech.edu
Jasjeet SekhonEugene Meyer Professor of Data Science, Political Science, and Statistics, Yale UniversityVerified email at yale.edu
Steven R HowardUniversity of California, BerkeleyVerified email at berkeley.edu
Aaditya RamdasStatistics and Machine Learning, Carnegie Mellon UniversityVerified email at stat.cmu.edu
David SchlegelSenior Scientist, Lawrence Berkeley National LabVerified email at lbl.gov
Dario BoffelliCedars Sinai Medical CenterVerified email at cshs.org
Edward M RubinScience CorpsVerified email at science-corps.org
Joseph OrgelProfessor of Biology, Physics and Biomedical EngineeringVerified email at iit.edu
Joan MariniSenior Investigator, NICHD, NIHVerified email at cc1.nichd.nih.gov
Andrew C. MillerResearch Scientist, AppleVerified email at apple.com
Michael BraunSouthern Methodist UniversityVerified email at smu.edu
Ryan GiordanoUC BerkeleyVerified email at berkeley.edu
Nilesh TripuraneniGoogle DeepMindVerified email at google.com
Matthew D. HoffmanResearch Scientist, Google ResearchVerified email at google.com
Daniel JeffaresSenior Lecturer, Department of Biology, University of YorkVerified email at york.ac.uk

Jon McAuliffe

Professor (Adj.) of Statistics, University of California, Berkeley

Verified email at stat.berkeley.edu

statistics computer science optimization machine learning bioinformatics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Variational inference: A review for statisticians DM Blei, A Kucukelbir, JD McAuliffe Journal of the American Statistical Association 112 (518), 859-877, 2017	5745	2017
Supervised topic models DM Blei, JD McAuliffe Arxiv preprint arXiv:1003.0783, 2010	2312*	2010
Convexity, classification, and risk bounds PL Bartlett, MI Jordan, JD McAuliffe Journal of the American Statistical Association 101 (473), 138-156, 2006	1800	2006
Phylogenetic shadowing of primate sequences to find functional regions of the human genome D Boffelli, J McAuliffe, D Ovcharenko, KD Lewis, I Ovcharenko, L Pachter, ... Science 299 (5611), 1391-1394, 2003	669	2003
Candidate cell and matrix interaction domains on the collagen fibril, the predominant protein of vertebrates SM Sweeney, JP Orgel, A Fertala, JD McAuliffe, KR Turner, GA Di Lullo, ... Journal of Biological Chemistry 283 (30), 21187-21197, 2008	343	2008
Time-uniform, nonparametric, nonasymptotic confidence sequences SR Howard, A Ramdas, J McAuliffe, J Sekhon The Annals of Statistics 49 (2), 1055-1080, 2021	292	2021
Variational inference for large-scale models of discrete choice M Braun, J McAuliffe Journal of the American Statistical Association 105 (489), 324-335, 2010	227	2010
Toward a protein profile of Escherichia coli: Comparison to its transcription profile RW Corbin, O Paliy, F Yang, J Shabanowitz, M Platt, CE Lyons Jr, K Root, ... Proceedings of the National Academy of Sciences 100 (16), 9232-9237, 2003	221	2003
Nonparametric empirical Bayes for the Dirichlet process mixture model JD McAuliffe, DM Blei, MI Jordan Statistics and Computing 16 (1), 5-14, 2006	177	2006
Time-uniform Chernoff bounds via nonnegative supermartingales SR Howard, A Ramdas, J McAuliffe, J Sekhon Probability Surveys 17, 257-317, 2020	140*	2020
Sulfur and nitrogen limitation in Escherichia coli K-12: specific homeostatic responses P Gyaneshwar, O Paliy, J McAuliffe, DL Popham, MI Jordan, S Kustu Journal of bacteriology 187 (3), 1074-1090, 2005	130	2005
Multiple-sequence functional annotation and the generalized hidden Markov phylogeny JD McAuliffe, L Pachter, MI Jordan Bioinformatics 20 (12), 1850-1860, 2004	78	2004
Lessons from Escherichia coli genes similarly regulated in response to nitrogen and sulfur limitation P Gyaneshwar, O Paliy, J McAuliffe, A Jones, MI Jordan, S Kustu Proceedings of the National Academy of Sciences 102 (9), 3453-3458, 2005	53	2005
Rao-Blackwellized stochastic gradients for discrete distributions R Liu, J Regier, N Tripuraneni, M Jordan, J Mcauliffe International Conference on Machine Learning, 4023-4031, 2019	42	2019
Cataloging the visible universe through Bayesian inference in Julia at petascale J Regier, K Fischer, K Pamnany, A Noack, J Revels, M Lam, S Howard, ... Journal of Parallel and Distributed Computing, 2019	41	2019
Celeste: Variational inference for a generative model of astronomical images J Regier, A Miller, J McAuliffe, R Adams, M Hoffman, D Lang, D Schlegel, ... Proceedings of the 32nd International Conference on Machine Learning, 2015	41	2015
Fast black-box variational inference through stochastic trust-region optimization J Regier, MI Jordan, J McAuliffe Advances in Neural Information Processing Systems, 2402-2411, 2017	29	2017
Long-and short-term selective forces on malaria parasite genomes S Nygaard, A Braunstein, G Malsen, S Van Dongen, PP Gardner, A Krogh, ... PLoS Genet 6 (9), e1001099, 2010	27	2010
Machine learning in low-level microarray analysis BIP Rubinstein, J McAuliffe, S Cawley, M Palaniswami, ... ACM SIGKDD Explorations Newsletter 5 (2), 130-139, 2003	23	2003
GLAD: a mixed-membership model for heterogeneous tumor subtype classification H Saddiki, J McAuliffe, P Flaherty Bioinformatics 31 (2), 225-232, 2015	21	2015

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