Michael Oberst
Michael Oberst
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Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
M Oberst, D Sontag
International Conference on Machine Learning (ICML) 2019, 2019
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
Regularizing towards causal invariance: Linear models with proxies
M Oberst, N Thams, J Peters, D Sontag
International Conference on Machine Learning, 8260-8270, 2021
Predicting human health from biofluid-based metabolomics using machine learning
ED Evans, C Duvallet, ND Chu, MK Oberst, MA Murphy, I Rockafellow, ...
Scientific reports 10 (1), 17635, 2020
Characterization of Overlap in Observational Studies
M Oberst, FD Johansson, D Wei, T Gao, G Brat, D Sontag, KR Varshney
23rd International Conference on Artificial Intelligence and Statistics …, 2020
Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes
S Boominathan, M Oberst, H Zhou, S Kanjilal, D Sontag
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020
Finding regions of heterogeneity in decision-making via expected conditional covariance
J Lim, CX Ji, M Oberst, S Blecker, L Horwitz, D Sontag
Advances in Neural Information Processing Systems 34, 15328-15343, 2021
Machine Learning for Health (ML4H) 2019: What Makes Machine Learning in Medicine Different?
AV Dalca, MBA McDermott, E Alsentzer, SG Finlayson, M Oberst, F Falck, ...
Machine Learning for Health Workshop, 1-9, 2020
Evaluating Robustness to Dataset Shift via Parametric Robustness Sets
N Thams, M Oberst, D Sontag
Neural Information Processing Systems (NeurIPS) 2022, 2022
AMR-UTI: Antimicrobial Resistance in Urinary Tract Infections (version 1.0.0)
M Oberst, S Boominathan, H Zhou, S Kanjilal, D Sontag
PhysioNet, 2020
Bias-robust Integration of Observational and Experimental Estimators
M Oberst, A D'Amour, M Chen, Y Wang, D Sontag, S Yadlowsky
arXiv preprint arXiv:2205.10467, 2022
Trajectory inspection: A method for iterative clinician-driven design of reinforcement learning studies
CX Ji, M Oberst, S Kanjilal, D Sontag
AMIA Summits on Translational Science Proceedings 2021, 305, 2021
Falsification before Extrapolation in Causal Effect Estimation
Z Hussain, M Oberst, MC Shih, D Sontag
Neural Information Processing Systems (NeurIPS) 2022, 2022
Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions
Z Hussain, MC Shih, M Oberst, I Demirel, D Sontag
International Conference on Artificial Intelligence and Statistics, 5869-5898, 2023
Counterfactual policy introspection using structural causal models
MK Oberst
Massachusetts Institute of Technology, 2019
Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2022 Symposium
S Hegselmann, H Zhou, Y Zhou, J Chien, S Nagaraj, N Hulkund, S Bhave, ...
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