1 citations · 2 across the 10 of their papers we have counts for
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Accounting for Missing Covariates in Heterogeneous Treatment Estimation
Khurram Yamin, Vibhhu Sharma, Ed Kennedy +1
Many applications of causal inference require using treatment effects estimated on a study population to make decisions in a separate target population. We consider the challenging…
Failure Modes of LLMs for Causal Reasoning on Narratives
Khurram Yamin, Shantanu Gupta, Gaurav R. Ghosal +2
The ability to robustly identify causal relationships is essential for autonomous decision-making and adaptation to novel scenarios. However, accurately inferring causal structure…
Orthogonal Causal Calibration
Justin Whitehouse, Christopher Jung, Vasilis Syrgkanis +2
Estimates of heterogeneous treatment effects such as conditional average treatment effects (CATEs) and conditional quantile treatment effects (CQTEs) play an important role in real…