AI RESEARCH
CAST: Causal Anchored Simplex Transport for Distribution-Valued Time Series
arXiv CS.LG
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ArXi:2605.16919v1 Announce Type: cross Many decision-facing stochastic systems are observed through aggregate distributions rather than scalar trajectories: queue occupancies, mobility shares, public-health mixtures, generation-source shares, ecological compositions, and air-quality severity profiles all live on the probability simplex and evolve over time. We study causal (online) forecasting for these distribution-valued time series and argue that the transition operator itself should be structured around the simplex. We.