
Differentiable Causal Discovery Under Unmeasured Confounding
The data drawn from biological, economic, and social systems are often c...
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Explaining The Behavior Of BlackBox Prediction Algorithms With Causal Learning
We propose to explain the behavior of blackbox prediction methods (e.g....
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Optimal Training of Fair Predictive Models
Recently there has been sustained interest in modifying prediction algor...
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Semiparametric Inference for Nonmonotone MissingNotatRandom Data: the No SelfCensoring Model
We study the identification and estimation of statistical functionals of...
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Causal Inference Under Interference And Network Uncertainty
Classical causal and statistical inference methods typically assume the ...
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A Potential Outcomes Calculus for Identifying Conditional PathSpecific Effects
The docalculus is a wellknown deductive system for deriving connection...
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Learning Optimal Fair Policies
We consider the problem of learning optimal policies from observational ...
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Comparing the Performance of Graphical Structure Learning Algorithms with TETRAD
In this report we describe a tool for comparing the performance of causa...
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Daniel Malinsky
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