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Debiased Machine Learning for Conformal Prediction of Counterfactual Outcomes Under Runtime Confounding

Barnatchez, Keith et al.
arXiv (OAI Expanded) · Papers
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machine-learning
Data-driven decision making frequently relies on predicting counterfactual outcomes. In practice, researchers commonly train counterfactual prediction models on a source dataset to inform decisions on a possibly separate target population. Conformal prediction has arisen as a popular method for prod
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