2025
Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference
UAI 2025
We introduce a novel stochastic variational inference method for Gaussian process ($\mathcal{GP}$) regression, by deriving a posterior over a learnable set of coresets: i.e., over pseudo-input/output, weighted pairs. Unlike former free-form variational families for stochastic inference, our coreset-