Recycling intermediate steps to improve Hamiltonian Monte Carlo

DOI10.1214/19-BA1171zbMath1480.62060arXiv1511.06925OpenAlexW3100346107MaRDI QIDQ2057341

Akihiko Nishimura, David B. Dunson

Publication date: 6 December 2021

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1511.06925

zbMATH Keywords

Markov chain Monte CarloBayesian inferenceHamiltonian Monte CarloRao-Blackwellizationmulti-proposal

Mathematics Subject Classification ID

Bayesian inference (62F15) Monte Carlo methods (65C05)

Related Items (3)

Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with State-Dependent Event Rates ⋮ Modified Hamiltonian Monte Carlo for Bayesian inference ⋮ Hamiltonian Monte Carlo with explicit, reversible, and volume-preserving adaptive step size control

Uses Software

• JAGS
• Stan
• PyMC
• BayesDA
• tmg
• NUTS

Cites Work

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• The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
• Split Hamiltonian Monte Carlo
• An improved acceptance procedure for the hybrid Monte Carlo algorithm
• Bayesian learning for neural networks
• On the geometric ergodicity of Hamiltonian Monte Carlo
• Optimal tuning of the hybrid Monte Carlo algorithm
• Handbook of Markov Chain Monte Carlo
• Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods
• Kinetic energy choice in Hamiltonian/hybrid Monte Carlo
• Equation of State Calculations by Fast Computing Machines

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