A stochastic version of Stein Variational Gradient Descent for efficient sampling

9 Feb 2019 Lei Li Yingzhou Li Jian-Guo Liu Zibu Liu Jianfeng Lu

We propose in this work RBM-SVGD, a stochastic version of Stein Variational Gradient Descent (SVGD) method for efficiently sampling from a given probability measure and thus useful for Bayesian inference. The method is to apply the Random Batch Method (RBM) for interacting particle systems proposed by Jin et al to the interacting particle systems in SVGD... (read more)

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