Conformal Treatment Effect Estimation Extended to Networked Interference
A new arXiv paper relaxes the standard no-interference assumption used in conformal counterfactual prediction, where one unit's treatment is assumed not to affect another's outcome. The authors develop an approach that produces prediction sets with finite-sample coverage guarantees for counterfactual outcomes and individual treatment effects when units interact within a network. This matters for settings such as social networks, marketplaces, and trials where spillover effects are common.