Atlas uses a Gaussian process (GP) surrogate model. A GP is a non-parametric probabilistic machine learning model which is most often used in regression settings. A GP is a collection of random variables such that the joint distribution of each finite subset of variables is multivariate normal. GPs are characterized by a mean, m(•) and covariance function, k(•, •) and are written