Wasserstein Parallel Transport for Predicting the Dynamics of Statistical Systems

ArXi:2603.23736v1 Announce Type: cross Many scientific systems, such as cellular populations or economic cohorts, are naturally described by probability distributions that evolve over time. Predicting how such a system would have evolved under different forces or initial conditions is fundamental to causal inference, domain adaptation, and counterfactual prediction. However, the space of distributions often lacks the vector space structure on which classical methods rely. To address this, we