A graph-regularized two-stage IV regression framework recovers sparse causal effects in networked exposures, accommodates partially invalid instruments, and provides non-asymptotic guarantees for estimation and selection.
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Network-aware IV Regression for Causal Node Discovery and Estimation
A graph-regularized two-stage IV regression framework recovers sparse causal effects in networked exposures, accommodates partially invalid instruments, and provides non-asymptotic guarantees for estimation and selection.