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cs.LG2026
Resource-Efficient Distributed Recursive Gaussian Processes
Josephine King, Ali Emre Balci, Raj Thilak Rajan
Gaussian processes (GPs) provide a flexible framework for learning unknown functions from noisy measurements while quantifying predictive uncertainty, making them well suited for e…
cs.LG2026
Consensus-based Recursive Multi-Output Gaussian Process
Yogesh Prasanna Kumar Rao, Tamas Keviczky, Raj Thilak Rajan
Multi-output Gaussian Processes provide principled uncertainty-aware learning of vector-valued fields but are difficult to deploy in large-scale, distributed, and streaming setting…