4 citations · 4 across the 3 of their papers we have counts for
3 papers
stat.ME2026
Causality-Encoded Diffusion Models for Interventional Sampling and Edge Inference
Li Chen, Xiaotong Shen, Wei Pan
Standard diffusion models are flexible estimators of complex distributions, but they do not encode causal structures and therefore do not by themselves support causal analysis. We…
stat.ME2025
Enhancing Causal Effect Estimation with Diffusion-Generated Data
Li Chen, Xiaotong Shen, Wei Pan
Estimating causal effects from observational data is inherently challenging due to the lack of observable counterfactual outcomes and even the presence of unmeasured confounding. T…
stat.ME2023★ 4 cited
Discovery and inference of a causal network with hidden confounding
Li Chen, Chunlin Li, Xiaotong Shen +1
This article proposes a novel causal discovery and inference method called GrIVET for a Gaussian directed acyclic graph with unmeasured confounders. GrIVET consists of an order-bas…