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06/08/2023
Causal Inference With Outcome-Dependent Missingness And Self-Censoring
We consider missingness in the context of causal inference when the outc...
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10/14/2020
Differentiable Causal Discovery Under Unmeasured Confounding
The data drawn from biological, economic, and social systems are often c...
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06/03/2020
Explaining The Behavior Of Black-Box Prediction Algorithms With Causal Learning
We propose to explain the behavior of black-box prediction methods (e.g....
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10/09/2019
Optimal Training of Fair Predictive Models
Recently there has been sustained interest in modifying prediction algor...
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09/04/2019
Semiparametric Inference for Non-monotone Missing-Not-at-Random Data: the No Self-Censoring Model
We study the identification and estimation of statistical functionals of...
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06/29/2019
Causal Inference Under Interference And Network Uncertainty
Classical causal and statistical inference methods typically assume the ...
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03/08/2019
A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects
The do-calculus is a well-known deductive system for deriving connection...
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09/06/2018
Learning Optimal Fair Policies
We consider the problem of learning optimal policies from observational ...
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07/27/2016
