Marginalised Gaussian Processes with Nested Sampling Fergus Simpson

Gaussian Process models are a rich distribution over functions with inductive biases controlled by a kernel function. Learning occurs through optimisation of the kernel hyperparameters using the marginal likelihood as the objective.