Jeremy Weiss — accepted AI-conference papers

2026

SurvHTE-Bench: A Benchmark for Heterogeneous Treatment Effect Estimation in Survival Analysis

Shahriar Noroozizadeh, Xiaobin Shen, Jeremy Weiss, George H. Chen

ICLR 2026poster

Estimating heterogeneous treatment effects (HTEs) from right-censored survival data is critical in high-stakes applications such as precision medicine and individualized policy-making. Yet, the survival analysis setting poses unique challenges for HTE estimation due to censoring, unobserved counterf…

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2023

Censored Fairness through Awareness

Wenbin Zhang, Tina Hernandez-Boussard, Jeremy Weiss

AAAI 2023technical

There has been increasing concern within the machine learning community and beyond that Artificial Intelligence (AI) faces a bias and discrimination crisis which needs AI fairness with urgency. As many have begun to work on this problem, most existing work depends on the availability of class label…

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