GPflow: A Gaussian Process Library using TensorFlow

@article{Matthews2017GPflowAG,
  title={GPflow: A Gaussian Process Library using TensorFlow},
  author={Alexander G. de G. Matthews and Mark van der Wilk and Tom Nickson and Keisuke Fujii and Alexis Boukouvalas and Pablo Le{\'o}n-Villagr{\'a} and Zoubin Ghahramani and James Hensman},
  journal={Journal of Machine Learning Research},
  year={2017},
  volume={18},
  pages={40:1-40:6}
}
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. 1. GPflow and TensorFlow are available as open source software under the Apache 2.0 license. 1 ar… CONTINUE READING
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