Data-Driven Covariate Selection for Nonparametric and Cycle-Agnostic Causal Effect Estimation
arXiv:2605.06385v1 Announce Type: new
Abstract: Estimating causal effects from observational data requires identifying valid adjustment sets. This task is especially challenging in realistic settings where latent confounding and feedback loops are pre…