St. John

Towards Improved Learning in Gaussian Processes: The Best of Two Worlds

2022 · arXiv (Cornell University)

Gaussian process training decomposes into inference of the (approximate) posterior and learning of the hyperparameters. For non-Gaussian (non-conjugate) likelihoods, two common choices for approximate inference are Expectation Propagation (EP) and Variational Inference (VI), which have …