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stat.ML2026
HyperMC: Multi-Fidelity Hyperparameter Tuning for Stochastic Gradient MCMC
Ming Tan, Xiyun Jiao
Stochastic gradient Markov chain Monte Carlo (SGMCMC) methods enable scalable Bayesian inference, but their performance depends strongly on hyperparameters such as the step size, m…
stat.ML2025
A Novel Framework Using Variational Inference with Normalizing Flows to Train Transport Reversible Jump Proposals
Pingping Yin, Xiyun Jiao
We propose a unified framework that employs variational inference (VI) with (conditional) normalizing flows (NFs) to train both between-model and within-model proposals for reversi…