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Multilevel Hamiltonian Monte Carlo/Evidence
Method evidence record

Multilevel Hamiltonian Monte Carlo

Multilevel Hamiltonian Monte Carlo (Multilevel HMC) combines the variance-reduction strategy of multilevel Monte Carlo with the efficient gradient-driven exploration of Hamiltonian Monte Carlo. By running coupled HMC chains at increasing levels of model fidelity or discretisation, it achieves accurate posterior estimates at a computational cost substantially lower than a single fine-level HMC chain.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Multilevel Hamiltonian Monte Carlo
Taxonomic method record · bayesian / bayesian
  • Beskos, A., Jasra, A., Law, K., Tempone, R., & Zhou, Y. (2017). Multilevel sequential Monte Carlo samplers. Stochastic Processes and their Applications, 127(5), 1417–1440. · DOI 10.1016/j.spa.2016.08.004
  • Neal, R. M. (2011). MCMC using Hamiltonian dynamics. In S. Brooks, A. Gelman, G. Jones, & X.-L. Meng (Eds.), Handbook of Markov Chain Monte Carlo (pp. 113–162). CRC Press. · URL
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Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyHamiltonian Monte Carlomachine-suggested · Relational suggestion, not evidence.Taxonomic bucketHierarchical Hamiltonian Monte Carlomachine-suggested · Relational suggestion, not evidence.See alsoMarkov Chain Monte Carlomachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMultilevel MCMCmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMultilevel Variational Inferencemachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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