David Sontag

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Fredrik D. JohanssonAssociate Professor, Chalmers University of TechnologyVerified email at chalmers.se
Yoni HalpernGoogleVerified email at google.com
Steven HorngClinical Lead for Machine Learning, Beth Israel Deaconess Medical CenterVerified email at bidmc.harvard.edu
Uri ShalitAssociate Professor, Technion - Israel Institute of TechnologyVerified email at technion.ac.il
Yoon KimAssistant Professor, MITVerified email at mit.edu
Yacine JerniteResearch Scientist, HuggingFaceVerified email at cs.nyu.edu
Tommi JaakkolaMITVerified email at csail.mit.edu
Monica AgrawalAssistant Professor, DukeVerified email at mit.edu
Hunter LangMITVerified email at mit.edu
Alexander M. RushAssociate Professor, Cornell UniversityVerified email at cornell.edu
Amir GlobersonTel Aviv UniversityVerified email at post.tau.ac.il
Rahul G. KrishnanUniversity of TorontoVerified email at cs.toronto.edu
Michael OberstJohns HopkinsVerified email at jhu.edu
Narges RazavianNew York University Medical CenterVerified email at nyumc.org
Irene Y. ChenAssistant Professor, UC Berkeley and UC San FranciscoVerified email at berkeley.edu
Larry NathansonAssistant Professor of Emergency Medicine, Harvard Medical SchoolVerified email at bidmc.harvard.edu
Hussein MozannarMassachusetts Institute of TechnologyVerified email at mit.edu
Nathan ShapiroBeth Israel Deaconess MEdical CenterVerified email at bidmc.harvard.edu
Aaron Smith-McLallenDirector - Data Science & Health Care AnalyticsVerified email at ibx.com
Ryen W. WhiteGeneral Manager, Deputy Lab Director, Microsoft ResearchVerified email at microsoft.com

David Sontag

Professor, Massachusetts Institute of Technology

Verified email at csail.mit.edu - Homepage

Machine Learning Healthcare Artificial Intelligence Graphical Models Approximate Inference


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Recurrent neural networks for multivariate time series with missing values Z Che, S Purushotham, K Cho, D Sontag, Y Liu Scientific reports 8 (1), 6085, 2018	2149	2018
Character-aware neural language models Y Kim, Y Jernite, D Sontag, AM Rush Thirtieth AAAI Conference on Artificial Intelligence, 2016	2136	2016
Estimating individual treatment effect: generalization bounds and algorithms U Shalit, F Johansson, D Sontag Proceedings of the International Conference on Machine Learning (ICML), 2017	1085	2017
Learning Representations for Counterfactual Inference FD Johansson, U Shalit, D Sontag 33rd International Conference on Machine Learning (ICML), 2016	819	2016
Causal Effect Inference with Deep Latent-Variable Models C Louizos, U Shalit, J Mooij, D Sontag, R Zemel, M Welling Neural Information Processing Systems (NIPS) 31, 2017	802	2017
BLOG: Probabilistic models with unknown objects B Milch, B Marthi, S Russell, D Sontag, DL Ong, A Kolobov Introduction to statistical relational learning, 373, 2007	615	2007
A practical algorithm for topic modeling with provable guarantees S Arora, R Ge, Y Halpern, D Mimno, A Moitra, D Sontag, Y Wu, M Zhu Proceedings of the International Conference on Machine Learning (ICML), 280--288, 2013	553	2013
Structured inference networks for nonlinear state space models RG Krishnan, U Shalit, D Sontag Thirty-First AAAI Conference on Artificial Intelligence, 2017	522	2017
Why is my classifier discriminatory? I Chen, FD Johansson, D Sontag NeurIPS, 2018	486	2018
Learning a health knowledge graph from electronic medical records M Rotmensch, Y Halpern, A Tlimat, S Horng, D Sontag Scientific reports 7 (1), 5994, 2017	449	2017
Guidelines for reinforcement learning in healthcare O Gottesman, F Johansson, M Komorowski, A Faisal, D Sontag, ... Nature medicine 25 (1), 16-18, 2019	434	2019
Deep kalman filters RG Krishnan, U Shalit, D Sontag arXiv preprint arXiv:1511.05121, 2015	424	2015
Learning Low-Dimensional Representations of Medical Concepts Y Choi, CYI Chiu, D Sontag Proceedings of the AMIA Summit on Clinical Research Informatics (CRI), 2016	370	2016
Tightening LP relaxations for MAP using message passing D Sontag, T Meltzer, A Globerson, T Jaakkola, Y Weiss Uncertainty in Artificial Intelligence (UAI) 24, 2008	367*	2008
Unsupervised learning of disease progression models X Wang, D Sontag, F Wang Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014	315	2014
Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning S Horng, DA Sontag, Y Halpern, Y Jernite, NI Shapiro, LA Nathanson PloS one 12 (4), e0174708, 2017	294	2017
Learning Bayesian network structure using LP relaxations T Jaakkola, D Sontag, A Globerson, M Meila Proceedings of the thirteenth international conference on artificial …, 2010	294	2010
Semi-amortized variational autoencoders Y Kim, S Wiseman, AC Miller, D Sontag, AM Rush ICML, 2018	282	2018
Large language models are few-shot clinical information extractors M Agrawal, S Hegselmann, H Lang, Y Kim, D Sontag arXiv preprint arXiv:2205.12689, 2022	259	2022
Population-level prediction of type 2 diabetes from claims data and analysis of risk factors N Razavian, S Blecker, AM Schmidt, A Smith-McLallen, S Nigam, ... Big Data 3 (4), 277-287, 2015	255	2015

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