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Generative orthogonal learning unlocks rate double robustness and quasi-oracle efficiency for estimating distributional treatment effects under complex time-varying confounding.
Unstable estimates in long-term treatment effect prediction? These orthogonal learners use custom overlap weights to improve robustness in low-overlap settings common in long-term outcomes.
