Variational inference for Gaussian processes

Gaussian Processes for Big Data

Variational Learning of Inducing Variables in Sparse Gaussian Processes

stochastic variational inference for Gaussian process models

GPs can be variationally decomposed to depend on a set of globally relevant inducing variables which factorize the model in the necessary manner to perform variational inference.