Statistical Inference for Causal Discovery under Selection and Latent Variables via Single-Target Interventions

Causal discovery from observational and interventional data becomes challenging in the presence of latent confounding and selection bias, where causal structure is no longer adequately represented by directed acyclic graphs over observed variables. Existing model-free methods often rely on an expone