Articles with public access mandates - David SontagLearn more
Available somewhere: 52
Estimating individual treatment effect: generalization bounds and algorithms
U Shalit, F Johansson, D Sontag
Proceedings of the International Conference on Machine Learning (ICML), 2017
Mandates: US National Science Foundation
Learning Representations for Counterfactual Inference
FD Johansson, U Shalit, D Sontag
33rd International Conference on Machine Learning (ICML), 2016
Mandates: US National Science Foundation
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
Mandates: Netherlands Organisation for Scientific Research, European Commission
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
Mandates: US National Institutes of Health
Structured inference networks for nonlinear state space models
RG Krishnan, U Shalit, D Sontag
Thirty-First AAAI Conference on Artificial Intelligence, 2017
Mandates: US National Science Foundation, US Department of Defense
Why is my classifier discriminatory?
I Chen, FD Johansson, D Sontag
NeurIPS, 2018
Mandates: US National Science Foundation, US Department of Defense
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
Mandates: US Department of Defense, US National Institutes of Health
Consistent estimators for learning to defer to an expert
H Mozannar, D Sontag
International conference on machine learning, 7076-7087, 2020
Mandates: US National Science Foundation
Support and invertibility in domain-invariant representations
FD Johansson, R Ranganath, D Sontag
AISTATS, 2019
Mandates: US Department of Defense
Electronic medical record phenotyping using the anchor and learn framework
Y Halpern, S Horng, Y Choi, D Sontag
Journal of the American Medical Informatics Association, 2016
Mandates: US National Institutes of Health, Natural Sciences and Engineering Research …
Tabllm: Few-shot classification of tabular data with large language models
S Hegselmann, A Buendia, H Lang, M Agrawal, X Jiang, D Sontag
International Conference on Artificial Intelligence and Statistics, 5549-5581, 2023
Mandates: US National Science Foundation
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
M Oberst, D Sontag
ICML, 2019
Mandates: US Department of Defense
Generalization bounds and representation learning for estimation of potential outcomes and causal effects
FD Johansson, U Shalit, N Kallus, D Sontag
Journal of Machine Learning Research 23 (166), 1-50, 2022
Mandates: US National Science Foundation, US Department of Defense, Knut and Alice …
Comparison of approaches for heart failure case identification from electronic health record data
S Blecker, SD Katz, LI Horwitz, G Kuperman, H Park, A Gold, D Sontag
JAMA cardiology 1 (9), 1014-1020, 2016
Mandates: US National Institutes of Health
Using anchors to estimate clinical state without labeled data
Y Halpern, Y Choi, S Horng, D Sontag
AMIA Annual Symposium Proceedings 2014, 606, 2014
Mandates: US National Institutes of Health
A decision algorithm to promote outpatient antimicrobial stewardship for uncomplicated urinary tract infection
S Kanjilal, M Oberst, S Boominathan, H Zhou, DC Hooper, D Sontag
Science translational medicine 12 (568), eaay5067, 2020
Mandates: US National Science Foundation
Detecting social and behavioral determinants of health with structured and free-text clinical data
DJ Feller, OJB Don't Walk, J Zucker, MT Yin, P Gordon, N Elhadad
Applied clinical informatics 11 (01), 172-181, 2020
Mandates: US National Institutes of Health
Teaching Humans When To Defer to a Classifier via Examplars
H Mozannar, A Satyanarayan, D Sontag
AAAI, 2022
Mandates: US National Science Foundation
A comparison of dimensionality reduction techniques for unstructured clinical text
Y Halpern, S Horng, LA Nathanson, NI Shapiro, D Sontag
ICML 2012 workshop on clinical data analysis, 2012
Mandates: US National Institutes of Health
Co-training improves prompt-based learning for large language models
H Lang, MN Agrawal, Y Kim, D Sontag
International Conference on Machine Learning, 11985-12003, 2022
Mandates: US National Science Foundation
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