GPflow: A Gaussian Process Library using TensorFlow

Alexander G.De G. Matthews, Mark Van Der Wilk, Tom Nickson, Keisuke Fujii, Alexis Boukouvalas, Pablo León-Villagrá, Zoubin Ghahramani, James Hensman

Research output: Contribution to journalArticlepeer-review

Abstract

GPflow is a Gaussian process library that uses TensorFlow for its core computations and Python for its front end.1 The distinguishing features of GPflow are that it uses variational inference as the primary approximation method, provides concise code through the use of automatic differentiation, has been engineered with a particular emphasis on software testing and is able to exploit GPU hardware.

Original languageEnglish
JournalJournal of Machine Learning Research
Volume18
Publication statusPublished - 30 Apr 2017

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