arXiv (Cornell University) · 2016 · 307 citations · 0 references
ComputingComputer EngineeringComputer ScienceComputer VisionMachine LearningParallel ComputingDeep LearningGaussian Process ModelingGaussian ProcessesGraphics Processing Unit ArchitectureGraphics Processing Unit ComputingVariational InferenceAutomatic DifferentiationDifferentiationFront-end DesignGpgpu ComputingGpgpu ProgrammingGpu Programming ModelsSoftware Testing ProcessVariational Gaussian Processes
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.