most citedFaster Hamiltonian Monte Carlo by Learning Leapfrog Scale: an offline randomized solution

13 citations · 13 across the 2 of their papers we have counts for

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2 papers

stat.CO2026

Optimal Sampling for Kernel Quadrature on Unbounded Domains

Edoardo Bandoni, Christian Robert, Julien Stoehr

Kernel quadrature is widely used to approximate integrals of smooth functions, with worst-case error typically decaying at the minimax rate for smoothness in dimensi…

stat.CO2018★ 13 cited

Faster Hamiltonian Monte Carlo by Learning Leapfrog Scale: an offline randomized solution

Changye Wu, Pierre Pudlo, Christian P. Robert +1

We introduce a Hamiltonian Monte Carlo (HMC) methodology based on an offline empirical calibration of randomized leapfrog parameters. The approach, referred to as eHMC, where \text…