Differential Equations and Nonlinear Analysis Seminar: Yulong Lu, Duke University, Understanding and accelerating statistical sampling algorithms: a PDE perspective
A fundamental problem in Bayesian inference and statistical machine learning is to efficiently sample from probability distributions. Standard Markov chain Monte Carlo methods could be prohibitively expensive due to various complexities of the target distribution, such as multimodality, high dimensionality, large datesets, etc. To improve the sampling efficiency, several new interesting ideas/methods have recently been proposed in the community…