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Data-Driven Covariate Selection for Nonparametric and Cycle-Agnostic Causal Effect Estimation
Local data-driven covariate selection via conditional independence remains sound and complete in cyclic causal models, enabling unified cycle-agnostic causal effect estimation.
Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026
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AI panel: 9 of 20 reviewers recommend it
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