Tag: po

PO-Flow: Flow-based Generative Models for Sampling Potential Outcomes and Counterfactuals arXiv:2505.16051v1 Announce Type: new Abstract: We propose PO-Flow, a novel continuous normalizing flow (CNF) framework for causal inference that jointly models potential outcomes and counterfactuals. Trained via flow matching, PO-Flow provides a unified framework for individualized potential outcome prediction, counterfactual predictions, and uncertainty-aware density learning.…