GPflow: A Gaussian process library using TensorFlow
Cited by 307Open Access
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.
Related Papers
No related papers found
Powered by citation graph analysis