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Accelerating Langevin Sampling with Birth-death
A fundamental problem in Bayesian inference and statistical machine learning is to efficiently sample from multimodal distributions.
Scaling limit of the Stein variational gradient descent: the mean field regime
We study an interacting particle system in $\mathbf{R}^d$ motivated by Stein variational gradient descent [Q. Liu and D. Wang, NIPS 2016], a deterministic algorithm for sampling from a given probability density with unknown normalization.
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