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stat.ML2026
Stochastic Gradient Variational Inference with Price's Gradient Estimator from Bures-Wasserstein to Parameter Space
Kyurae Kim, Qiang Fu, Yi-An Ma +2
For approximating a target distribution given only its unnormalized log-density, stochastic gradient-based variational inference (VI) algorithms are a popular approach. For example…
stat.ML2024
MCMC-driven learning
Alexandre Bouchard-Côté, Trevor Campbell, Geoff Pleiss +1
This paper is intended to appear as a chapter for the Handbook of Markov Chain Monte Carlo. The goal of this chapter is to unify various problems at the intersection of Markov chai…