$\beta$-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap

no code implementations • ICLR 2022 • Pengzhou Abel Wu, Kenji Fukumizu

We use a latent variable to model a prognostic score which is widely used in biostatistics and sufficient for TEs; i. e., we build a generative prognostic model.

Causal Inference

Identifying and Estimating Causal Effects under Weak Overlap by Generative Prognostic Model

no code implementations • NeurIPS 2021 • Pengzhou Abel Wu, Kenji Fukumizu

As an important problem of causal inference, we discuss the identification and estimation of treatment effects (TEs) under weak overlap, i. e., subjects with certain features all belong to a single treatment group.

Causal Inference counterfactual +1