Sparse GP Approximations

Sparse GP Approximations

Abstract

I present an introduction to pseudo-input methods for sparse GP approximations. I derive the variational lower bounds for SGPR and SVGP and give some intution for how they should be interpreted.

Type
Publication
Bayesian methods reading group
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Markus Kaiser
PhD candidate in Bayesian Machine Learning

My research interests include hierarchical Bayesian modelling, Gaussian Processes and scalable Bayesian Inference.