3 papers
stat.ML2026
Anchored Stein Variational Gradient Descent Algorithm for Non-smooth Sampling
Thanh Dang, Matthew X. Burns, Jiaming Liang
We introduce a Stein variational framework for sampling from a target density when the target potential is possibly non-smooth. The key idea is to introduce a…
stat.ML2026
Constrained and Composite Sampling via Proximal Sampler
Thanh Dang, Jiaming Liang
We study two log-concave sampling problems: constrained sampling and composite sampling. First, we consider sampling from a target distribution with density proportional to $\exp(-…
cs.DS2025
Oracle-based Uniform Sampling from Convex Bodies
Thanh Dang, Jiaming Liang
We propose new Markov chain Monte Carlo algorithms to sample a uniform distribution on a convex body . Our algorithms are based on the proximal sampler, which uses Gibbs samplin…