GPflow: A Gaussian process library using TensorFlow
A. G. Matthews
Mark van der Wilk
T. Nickson
Keisuke Fujii
A. Boukouvalas
Pablo León-Villagrá
Zoubin Ghahramani
J. Hensman

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.
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