“Tuning-Free Generalized Hamiltonian Monte Carlo”

Matt Hoffman and Pavel Sountsov write: Hamiltonian Monte Carlo (HMC) has become a go-to family of Markov chain Monte Carlo (MCMC) algorithms for Bayesian inference problems, in part because we have good procedures for automatically tuning its parameters. Much less … Continue reading → …