Associate Professor, Beijing Technology and Business University
2 papers at NeurIPS 2025
Learning the individualized treatment effects under the assumption of rank preservation.
We propose a novel influence-based adaptive sample borrowing approach to enhance treatment effect estimation in RCTs by effectively incorporating external controls.