Faster Hamiltonian Monte Carlo by learning leapfrog scale: an offline randomized solution

Changye Wu, Pierre Pudlo, Christian P. Robert, Julien Stoehr

Open source

DOI: 10.1007/s11222-026-10972-z
Published: 2026-09-23
Container: Statistics and Computing
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s11222-026-10972-z,
  title = {Faster Hamiltonian Monte Carlo by learning leapfrog scale: an offline randomized solution},
  author = {Changye Wu and Pierre Pudlo and Christian P. Robert and Julien Stoehr},
  year = {2026},
  journal = {Statistics and Computing},
  doi = {10.1007/s11222-026-10972-z},
  url = {https://doi.org/10.1007/s11222-026-10972-z}
}

RIS

TY  - JOUR
TI  - Faster Hamiltonian Monte Carlo by learning leapfrog scale: an offline randomized solution
AU  - Changye Wu
AU  - Pierre Pudlo
AU  - Christian P. Robert
AU  - Julien Stoehr
PY  - 2026
JO  - Statistics and Computing
DO  - 10.1007/s11222-026-10972-z
UR  - https://doi.org/10.1007/s11222-026-10972-z
ER  -

APA

Wu, C., Pudlo, P., Robert, C. P., & Stoehr, J. (2026). Faster Hamiltonian Monte Carlo by learning leapfrog scale: an offline randomized solution. Statistics and Computing. https://doi.org/10.1007/s11222-026-10972-z

Source records

crossref · retrieved 2026-11-10T13:34:17.840Z