4 papers
Automatic, Debiased, and Invariant Counterfactual Generation under General Interventions
Raphael C Kim, Jingsen Zhu, Ramin Zabih +1
Generative models for counterfactual outcomes have great potential to support decision-making under complex interventions, but existing approaches are limited by unstable estimatio…
Data-Adaptive and Model-Robust Covariate Adjustment for Time-to-Event Outcomes in Stratified Randomized Trials
Raphael C. Kim, Brian Gilbert, Ramin Zabih +2
Time-to-event outcomes are commonly used as primary endpoints in randomized clinical trials. Despite this, relatively little work incorporates baseline covariate information while…
Fair Policy Learning under Bipartite Network Interference: Learning Fair and Cost-Effective Environmental Policies
Raphael C. Kim, Rachel C. Nethery, Kevin L. Chen +1
Numerous studies have shown the harmful effects of airborne pollutants on human health. Vulnerable groups and communities often bear a disproportionately larger health burden due t…
Towards Optimal Environmental Policies: Policy Learning under Arbitrary Bipartite Network Interference
Raphael C. Kim, Falco J. Bargagli-Stoffi, Kevin L. Chen +1
The substantial effect of air pollution on cardiovascular disease and mortality burdens is well-established. Emissions-reducing interventions on coal-fired power plants -- a major…