AI RESEARCH

Causal Optimal Coupling for Gaussian Input-Output Distributional Data

arXiv CS.LG

ArXi:2604.01406v1 Announce Type: cross We study the problem of identifying an optimal coupling between input-output distributional data generated by a causal dynamical system. The coupling is required to satisfy prescribed marginal distributions and a causality constraint reflecting the temporal structure of the system. We formulate this problem as a Schr"odinger Bridge, which seeks the coupling closest - in Kullback-Leibler divergence - to a given prior while enforcing both marginal and causality constraints.