Yi Li

Estimating heterogeneous treatment effects with survival outcomes via a deep survival learner

Abstract Estimating heterogeneous treatment effects in survival settings is complicated by right censoring as well as the time-varying nature of the estimand. While the conditional average treatment effect (CATE) provides a natural target, most existing approaches focus on a sing...