CRMGP enables fully distributed parallel learning of multi-output Gaussian processes via recursive inference and neighbor-to-neighbor consensus, preserving output correlations and uncertainty calibration.
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Consensus-based Recursive Multi-Output Gaussian Process
CRMGP enables fully distributed parallel learning of multi-output Gaussian processes via recursive inference and neighbor-to-neighbor consensus, preserving output correlations and uncertainty calibration.