Search Results for author:
Found 3 papers, 0 papers with code
β-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap
As an important problem in causal inference, we discuss the identification and estimation of treatment effects (TEs) under limited overlap; that is, when subjects with certain features belong to a single treatment group.
Towards Principled Causal Effect Estimation by Deep Identifiable Models
As an important problem in causal inference, we discuss the estimation of treatment effects (TEs).
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding
As an important problem of causal inference, we discuss the identification and estimation of treatment effects under unobserved confounding.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
