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We study the Stein Variational Gradient Descent (SVGD) algorithm, which optimises a set of particles to approximate a target probability distribution $\pi\propto e^{-V}$ on $\mathbb{R}^d$.
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Scaling limit of the stein variational gradient descent: The mean field regime
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Advances in variational inference
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