Gaussian Process-based learning with new MCMC-based implementation of Wishart prior on correlation matrix

In probabilstic supervised learning of an input-output relationship - as a sample function of a Gaussian Process (GP) - priors are typically specified for the hyperparameters of the kernel that parametrises the covariance function of the GP, where the induced covariance matrix of the (resulting mult...