Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference

Mert Ketenci, Adler Perotte, Noémie Elhadad +1

We introduce a novel stochastic variational inference method for Gaussian process ($\mathcal{G}\mathcal{P}$) regression, by deriving a posterior over a learnable set of coresets: i.e., over…