20 citations · 29 across the 2 of their papers we have counts for
3 papers
math.ST2019★ 9 cited
An empirical -Wishart prior for sparse high-dimensional Gaussian graphical models
Chang Liu, Ryan Martin
In Gaussian graphical models, the zero entries in the precision matrix determine the dependence structure, so estimating that sparse precision matrix and, thereby, learning this un…
stat.ML2018
Understanding and Accelerating Particle-Based Variational Inference
Chang Liu, Jingwei Zhuo, Pengyu Cheng +3
Particle-based variational inference methods (ParVIs) have gained attention in the Bayesian inference literature, for their capacity to yield flexible and accurate approximations.…
stat.ML2017★ 20 cited
Riemannian Stein Variational Gradient Descent for Bayesian Inference
Chang Liu, Jun Zhu
We develop Riemannian Stein Variational Gradient Descent (RSVGD), a Bayesian inference method that generalizes Stein Variational Gradient Descent (SVGD) to Riemann manifold. The be…