# Couplings for Multinomial Hamiltonian Monte Carlo

@inproceedings{Xu2021CouplingsFM, title={Couplings for Multinomial Hamiltonian Monte Carlo}, author={Kai Xu and Tor Erlend Fjelde and Charles Sutton and Hong Ge}, booktitle={AISTATS}, year={2021} }

Hamiltonian Monte Carlo (HMC) is a popular sampling method in Bayesian inference. Recently, Heng & Jacob (2019) studied Metropolis HMC with couplings for unbiased Monte Carlo estimation, establishing a generic parallelizable scheme for HMC. However, in practice a different HMC method, multinomial HMC, is considered as the go-to method, e.g. as part of the no-U-turn sampler. In multinomial HMC, proposed states are not limited to end-points as in Metropolis HMC; instead points along the entire… Expand

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