Tomoki Matsumoto

Parallel MCMC via machine learning classification and a Kullback–Leibler divergence criterion

This study develops a Kullback–Leibler (KL) divergence-based criterion that does not require calculating the full-posterior density and can be calculated using only information from the sub-posterior densities, which are generally obtained after implementing MCMC.