Author name: Stefano Cortinovis, Laurence Aitchison, Stefanos Eleftheriadis, Mark van der Wilk

arXiv:2604.00697v1 Announce Type: new
Abstract: Gaussian processes (GPs) offer appealing properties but are costly to train at scale. Sparse variational GP (SVGP) approximations reduce cost yet still rely on Cholesky decompositions of kernel matrices,…