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HiMAP: Hilbert Mass-Addressed Parameterization for Multivariate Barycenters and Frećhet Regression
Learning from multivariate distribution-valued data requires both averaging distributions and predicting them from covariates. Positive barycenters and Fréchet regression impose different closure requirements. Regression weights can be negative, yet every fitted value must remain a probability law.
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