See my Google Scholar Page for an up-to-date list of publications.

Journal Papers

A decision algorithm to promote outpatient antimicrobial stewardship for uncomplicated urinary tract infection
Sanjat Kanjilal, Michael Oberst, Sooraj Boominathan, Helen Zhou, David C. Hooper, David Sontag
Science Translational Medicine, 2020
[article], [code], [dataset]

Predicting Human Health from Biofluid-Based Metabolomics using Machine Learning
Ethan D. Evans, Claire Duvallet, Nathaniel D. Chu, Michael Oberst, Michael A.Murphy, Isaac Rockafellow, David Sontag, Eric J. Alm
Scientific Reports, 2020

Conference Papers

Evaluating Robustness to Dataset Shift via Parametric Robustness Sets
Nikolaj Thams*, Michael Oberst*, David Sontag
Neural Information Processing Systems (NeurIPS), 2022
[paper], [code] *Equal Contribution, order determined by coin flip

Falsification before Extrapolation in Causal Effect Estimation
Zeshan Hussain*, Michael Oberst*, Ming-Chieh Shih*, David Sontag
Neural Information Processing Systems (NeurIPS), 2022
[paper] *Equal Contribution, alphabetical order

Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance
Justin Lim*, Christina X. Ji*, Michael Oberst*, Saul Blecker, Leora Horwitz, David Sontag
Neural Information Processing Systems (NeurIPS), 2021
[paper], [video], [code] *Equal Contribution

Regularizing towards Causal Invariance: Linear Models with Proxies
Michael Oberst, Nikolaj Thams, Jonas Peters, David Sontag
International Conference on Machine Learning (ICML), 2021
[paper], [video], [slides], [poster], [code]

Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies
Christina X. Ji*, Michael Oberst*, Sanjat Kanjilal, David Sontag
AMIA Virtual Informatics Summit, 2021
[paper], [video], [code] *Equal Contribution

Characterization of Overlap in Observational Studies
Michael Oberst*, Fredrik D. Johansson*, Dennis Wei*, Tian Gao, Gabriel Brat, David Sontag, Kush R. Varshney
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
[paper], [video], [code] *Equal Contribution

Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes
Sooraj Boominathan, Michael Oberst, Helen Zhou, Sanjat Kanjilal, David Sontag
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
[paper], [video], [code], [dataset]

Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
Michael Oberst, David Sontag
International Conference on Machine Learning (ICML), 2019
[paper], [slides], [poster], [video]


Bias-robust Integration of Observational and Experimental Estimators
Michael Oberst, Alexander D’Amour, Minmin Chen, Yuyan Wang, David Sontag, Steve Yadlowsky
Oral presentation at the American Causal Inference Conference (ACIC), 2022

Other Publications

Counterfactual Policy Introspection using Structural Causal Models
Michael Oberst
M.S. Thesis in EECS, MIT
[full text], [note on errata]