3 papers
math.ST2025
Spectral gap bounds for reversible hybrid Gibbs chains
Qian Qin, Nianqiao Ju, Guanyang Wang
Hybrid Gibbs samplers represent a prominent class of approximated Gibbs algorithms that utilize Markov chains to approximate conditional distributions, with the Metropolis-within-G…
cs.LG2024
A phase transition in sampling from Restricted Boltzmann Machines
Youngwoo Kwon, Qian Qin, Guanyang Wang +1
Restricted Boltzmann Machines are a class of undirected graphical models that play a key role in deep learning and unsupervised learning. In this study, we prove a phase transition…
stat.ML2024
Neural-g: A Deep Learning Framework for Mixing Density Estimation
Shijie Wang, Saptarshi Chakraborty, Qian Qin +1
Mixing (or prior) density estimation is an important problem in machine learning and statistics, especially in empirical Bayes -modeling where accurately estimating the prior is…