1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ME2024★ 1 cited
A General Causal Inference Framework for Cross-Sectional Observational Data
Yonghe Zhao, Huiyan Sun
Causal inference methods for observational data are highly regarded due to their wide applicability. While there are already numerous methods available for de-confounding bias, the…
cs.LG2023
VLUCI: Variational Learning of Unobserved Confounders for Counterfactual Inference
Yonghe Zhao, Qiang Huang, Siwei Wu +2
Causal inference plays a vital role in diverse domains like epidemiology, healthcare, and economics. De-confounding and counterfactual prediction in observational data has emerged…
stat.ME2023
Does Misclassifying Non-confounding Covariates as Confounders Affect the Causal Inference within the Potential Outcomes Framework?
Yonghe Zhao, Qiang Huang, Shuai Fu +1
The Potential Outcome Framework (POF) plays a prominent role in the field of causal inference. Most causal inference models based on the POF (CIMs-POF) are designed for eliminating…