A CATE estimator is proposed that uses outcome-only RCT data to regularize observational-data predictions via marginal and projection balancing, with experiments on synthetic and real datasets.
Probability and measure
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Conditional Average Treatment Effect Estimation Under Hidden Confounders
A CATE estimator is proposed that uses outcome-only RCT data to regularize observational-data predictions via marginal and projection balancing, with experiments on synthetic and real datasets.