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FedUP: Uncertainty-Aware Personalized Federated Learning via Probabilistic Prototypes
FedUP is an uncertainty-aware personalized federated learning framework that models prototypes as probability distributions and aggregates prototype distributions through reliability-informed barycenters on the statistical manifold, suppressing unreliable contributions while preserving geometric structure.