CUED Publications database

GPflow: A Gaussian Process Library using TensorFlow

Matthews, AGDG and Van Der Wilk, M and Nickson, T and Fujii, K and Boukouvalas, A and León-Villagrá, P and Ghahramani, Z and Hensman, J (2017) GPflow: A Gaussian Process Library using TensorFlow. Journal of Machine Learning Research, 18. ISSN 1532-4435

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© 2017 Alexander G. de G. Matthews, Mark van der Wilk, Tom Nickson, Keisuke Fujii, Alexis Boukouvalas, Pablo León-Villagrá, Zoubin Ghahramani, and James Hensman. 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.

Item Type: Article
Divisions: Div F > Computational and Biological Learning
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:26
Last Modified: 10 Apr 2021 00:47