Tommi Jaakkola

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Regina BarzilayProfessor of EECS, MITVerified email at csail.mit.edu
Wengong JinBroad Institute of MIT and HarvardVerified email at csail.mit.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Klavs F.JensenChemical Engineering, MITVerified email at mit.edu
Nathan SrebroProfessor, TTIC and University of ChicagoVerified email at ttic.edu
David Alvarez-MelisHarvard University & Microsoft ResearchVerified email at seas.harvard.edu
Lawrence K. SaulSenior Research Scientist, Flatiron InstituteVerified email at flatironinstitute.org
Alan S. WillskyProfessor of EECS, MITVerified email at mit.edu
Connor W. ColeyMassachusetts Institute of TechnologyVerified email at mit.edu
Amir GlobersonTel Aviv UniversityVerified email at post.tau.ac.il
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Martin WainwrightProfessor, EECS/Mathematics, Massachusetts Institute of TechnologyVerified email at mit.edu
William H. GreenHoyt C. Hottel Professor of Chemical Engineering, MITVerified email at mit.edu
Tao LeiGoogleVerified email at google.com
David SontagProfessor, Massachusetts Institute of TechnologyVerified email at csail.mit.edu
Bowen JingMassachusetts Institute of TechnologyVerified email at mit.edu
Ziv Bar-JosephProfessor of Computational Biology and Machine Learning, School of Computer Science, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Richard YoungProfessor of Biology, MITVerified email at wi.mit.edu
Kyle SwansonStanford UniversityVerified email at stanford.edu
Gabriele CorsoPhD Student, MITVerified email at mit.edu

Tommi Jaakkola

Other namesTommi S. Jaakkola

MIT

Verified email at csail.mit.edu - Homepage

machine learning natural language processing biomolecular design


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
An introduction to variational methods for graphical models MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul Machine learning 37, 183-233, 1999	4763	1999
Exploiting generative models in discriminative classifiers T Jaakkola, D Haussler Advances in neural information processing systems 11, 1998	2088	1998
A deep learning approach to antibiotic discovery JM Stokes, K Yang, K Swanson, W Jin, A Cubillos-Ruiz, NM Donghia, ... Cell 180 (4), 688-702. e13, 2020	1932	2020
Junction tree variational autoencoder for molecular graph generation W Jin, R Barzilay, T Jaakkola International conference on machine learning, 2323-2332, 2018	1605	2018
Analyzing learned molecular representations for property prediction K Yang, K Swanson, W Jin, C Coley, P Eiden, H Gao, A Guzman-Perez, ... Journal of chemical information and modeling 59 (8), 3370-3388, 2019	1429	2019
Maximum-margin matrix factorization N Srebro, J Rennie, T Jaakkola Advances in neural information processing systems 17, 2004	1420	2004
Convergence of stochastic iterative dynamic programming algorithms T Jaakkola, M Jordan, S Singh Advances in neural information processing systems 6, 1993	1355	1993
Towards robust interpretability with self-explaining neural networks D Alvarez Melis, T Jaakkola Advances in neural information processing systems 31, 2018	1072	2018
Weighted low-rank approximations N Srebro, T Jaakkola Proceedings of the 20th international conference on machine learning (ICML …, 2003	1035	2003
Convergence results for single-step on-policy reinforcement-learning algorithms S Singh, T Jaakkola, ML Littman, C Szepesvári Machine learning 38, 287-308, 2000	1027	2000
Rationalizing neural predictions T Lei, R Barzilay, T Jaakkola arXiv preprint arXiv:1606.04155, 2016	953	2016
Variational message passing. J Winn, CM Bishop, T Jaakkola Journal of Machine Learning Research 6 (4), 2005	948	2005
Style transfer from non-parallel text by cross-alignment T Shen, T Lei, R Barzilay, T Jaakkola Advances in neural information processing systems 30, 2017	890	2017
Approximate inference in additive factorial hmms with application to energy disaggregation JZ Kolter, T Jaakkola Artificial intelligence and statistics, 1472-1482, 2012	849	2012
Serial regulation of transcriptional regulators in the yeast cell cycle I Simon, J Barnett, N Hannett, CT Harbison, NJ Rinaldi, TL Volkert, ... Cell 106 (6), 697-708, 2001	847	2001
Partially labeled classification with Markov random walks M Szummer, T Jaakkola Advances in neural information processing systems 14, 2001	839	2001
MAP estimation via agreement on trees: message-passing and linear programming MJ Wainwright, TS Jaakkola, AS Willsky IEEE transactions on information theory 51 (11), 3697-3717, 2005	817	2005
Computational discovery of gene modules and regulatory networks Z Bar-Joseph, GK Gerber, TI Lee, NJ Rinaldi, JY Yoo, F Robert, ... Nature biotechnology 21 (11), 1337-1342, 2003	803	2003
Bayesian parameter estimation via variational methods TS Jaakkola, MI Jordan Statistics and Computing 10, 25-37, 2000	802	2000
An introduction to variational methods for graphical models MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul Learning in graphical models, 105-161, 1998	760	1998

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