AI RESEARCH
Sequential Transport for Causal Mediation Analysis
arXiv CS.LG
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ArXi:2603.15182v1 Announce Type: cross We propose sequential transport (ST), a distributional framework for mediation analysis that combines optimal transport (OT) with a mediator directed acyclic graph (DAG). Instead of relying on cross-world counterfactual assumptions, ST constructs unit-level mediator counterfactuals by minimally transporting each mediator, either marginally or conditionally, toward its distribution under an alternative treatment while preserving the causal dependencies encoded by the.