2023
Proximal Causal Learning of Conditional Average Treatment Effects
ICML 2023poster
Efficiently and flexibly estimating treatment effect heterogeneity is an important task in a wide variety of settings ranging from medicine to marketing, and there are a considerable number of promising conditional average treatment effect estimators currently available. These, however, typically re…