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JMLR 2017

GPflow: A Gaussian Process Library using TensorFlow

Journal Article Articles Artificial Intelligence · Machine Learning

Abstract

GPflow is a Gaussian process library that uses TensorFlow for its core computations and Python for its front end. 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. [abs] [ pdf ][ bib ] [ code ] [ webpage ] &copy JMLR 2017. ( edit, beta )

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Context

Venue
Journal of Machine Learning Research
Archive span
2000-2026
Indexed papers
4180
Paper id
929001537217567565