2 papers
cs.LG2026
Regularizing Extrapolation in Causal Inference
David Arbour, Harsh Parikh, Bijan Niknam +3
Many common estimators in machine learning and causal inference are linear smoothers, where the prediction is a weighted average of the training outcomes. Some estimators, such as…
stat.ME2026
Demystifying Proximal Causal Inference
Grace V. Ringlein, Trang Quynh Nguyen, Peter P. Zandi +2
Proximal causal inference (PCI) has emerged as a promising framework for identifying and estimating causal effects in the presence of unobserved confounders. While many traditional…