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Tensorflow implementation of Stein Variational Gradient Descent (SVGD)

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Stein Variational Gradient Descent

Tensorflow implementation of Stein Variational Gradient Descent (SVGD)

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Description

"SVGD is a general purpose variational inference algorithm that forms a natural counterpart of gradient descent for optimization. SVGD iteratively transports a set of particles to match with the target distribution, by applying a form of functional gradient descent that minimizes the KL divergence."

Link

  • For official implementation in Matlab and Theano, please visit the authors' project website - SVGD.
  • Paper: Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm, NIPS2017 arXiv.

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Tensorflow implementation of Stein Variational Gradient Descent (SVGD)

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