A gradient-based and determinant-free framework for fully Bayesian Gaussian process regression

P. Michael Kielstra, Michael Lindsey

Gaussian Process Regression (GPR) is widely used for inferring functions from noisy data. GPR crucially relies on the choice of a kernel, which might be specified in terms of a col…