The Theory and Practice of Highly Scalable Gaussian Process Regression with Nearest Neighbours
arXiv:2604.07267v1 Announce Type: new
Abstract: Gaussian process ($GP$) regression is a widely used non-parametric modeling tool, but its cubic complexity in the training size limits its use on massive data sets. A practical remedy is to predict using…