Stochastic Gradient Geodesic MCMC Methods

Chang Liu, Jun Zhu, Yang Song

Neural Information Processing Systems 

We propose two stochastic gradient MCMC methods for sampling from Bayesian posterior distributions defined on Riemann manifolds with a known geodesic flow, e.g.