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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…
cs.LG2023★ 6 cited
De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial Network
Yonghe Zhao, Qiang Huang, Haolong Zeng +2
Counterfactual inference for continuous rather than binary treatment variables is more common in real-world causal inference tasks. While there are already some sample reweighting…