AI RESEARCH
Consensus-based Recursive Multi-Output Gaussian Process
arXiv CS.LG
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ArXi:2604.10146v1 Announce Type: new Multi-output Gaussian Processes provide principled uncertainty-aware learning of vector-valued fields but are difficult to deploy in large-scale, distributed, and streaming settings due to their computational and centralized nature. This paper proposes a Consensus-based Recursive Multi-Output Gaussian Process (CRMGP) framework that combines recursive inference on shared basis vectors with neighbour-to-neighbour information-consensus updates.