3 papers
stat.ME2026
Accelerating Bayesian Phylogenetic Inference via Delayed Acceptance Sequential Monte Carlo with Random Forest Surrogates
Wentao Yu, Shijia Wang
In Bayesian phylogenetics, our goal is to estimate the posterior distribution over phylogenetic trees. Markov chain Monte Carlo methods are widely used to approximate the phylogene…
stat.CO2026
A multifidelity approximate Bayesian computation with pre-filtering
Xuefei Cao, Shijia Wang, Yongdao Zhou
Approximate Bayesian Computation (ABC) methods often require extensive simulations, resulting in high computational costs. This paper focuses on multifidelity simulation models and…
stat.CO2025
An adaptive approximate Bayesian computation MCMC with Global-Local proposals
Xuefei Cao, Shijia Wang, Yongdao Zhou
In this paper, we address the challenge of Markov Chain Monte Carlo (MCMC) algorithms within the approximate Bayesian Computation (ABC) framework, which often get trapped in local…