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20222026
most citedCombining T-learning and DR-learning: a framework for oracle-efficient estimation of causal contrasts

2 citations · 4 across the 8 of their papers we have counts for

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stat.ML2026

ProximalFM: Amortized Proximal Causal Inference under Hidden Confounding

Christophe Muller, Ayub Kharel, Alex Luedtke +7

Standard causal identification methods often assume no unmeasured confounding and can fail when relevant confounders are unobserved. Proximal causal inference instead uses proxy va…

stat.ML2024★ 2 cited

Combining T-learning and DR-learning: a framework for oracle-efficient estimation of causal contrasts

Lars van der Laan, Marco Carone, Alex Luedtke

We introduce efficient plug-in (EP) learning, a novel framework for the estimation of heterogeneous causal contrasts, such as the conditional average treatment effect and condition…