Representation Learning for Sample-Efficient CATE Estimation by Leveraging Multiple Outcomes
Estimating conditional average treatment effects (CATE) enables efficient targeting of interventions, but many applications have limited experimental samples, making it difficult to estimate heterogeneous effects from high-dimensional covariates. In such settings, policymakers and medical practitioners often succumb to...
Maitreyi Swaroop, Shikha Bhat, Samantha Rodriguez et al.
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