Multi-fidelity Hamiltonian Monte Carlo

arXiv:2405.05033v1 Announce Type: cross
Abstract: Numerous applications in biology, statistics, science, and engineering require generating samples from high-dimensional probability distributions. In recent years, the Hamiltonian Monte Carlo (HMC) method has emerged as a state-of-the-art Markov chain Monte Carlo technique, exploiting the shape of such high-dimensional target distributions to efficiently generate samples. Despite its impressive empirical success and increasing popularity, its wide-scale adoption remains limited due to the high computational cost of gradient calculation. Moreover, applying this method is impossible when …

abstract applications art arxiv biology cs.ce cs.lg engineering fidelity generate hamiltonian monte carlo markov probability samples science state statistics stat.ml success type