Stable Blanket with Hidden Variables and Cycles

ArXi:2605.01856v1 Announce Type: cross Stabilized regression aims to identify a set of predictors whose conditional relationship with a response variable remains invariant across different environments. Existing graphical characterizations of the stable blanket are mainly developed for structural causal models (SCMs) without hidden variables or causal cycles. However, latent variables and feedback relationships naturally arise in many applications, and they can change both the Marko blanket and the set of predictors that remain stable under interventions.