Cyclic Counterfactuals under Shift–Scale Interventions

Most counterfactual inference frameworks traditionally assume acyclic structural causal models (SCMs), i.e., directed acyclic graphs (DAGs). However, many real-world systems (e.g., biological systems) contain feedback loops or cyclic dependencies that violate acyclicity.

In this work, we study counterfactual inference in cyclic SCMs under shift–scale interventions, i.e., soft, policy-style changes that rescale and/or shift a variable’s mechanism.