Forward Event-Chain Monte Carlo: Fast Sampling by Randomness Control in Irreversible Markov Chains

DOI10.1080/10618600.2020.1750417OpenAlexW3015112815MaRDI QIDQ5066738

Alain Durmus, Manon Michel, Stéphane Sénécal

Publication date: 30 March 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1702.08397

zbMATH Keywords

Markov chain Monte Carlo methodpiecewise deterministic Markov processhigh-dimensional sampling

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (11)

Sparse hard-disk packings and local Markov chains ⋮ On explicit \(L^2\)-convergence rate estimate for piecewise deterministic Markov processes in MCMC algorithms ⋮ Direction-sweep Markov chains ⋮ Exact targeting of Gibbs distributions using velocity-jump processes ⋮ Transport Monte Carlo: High-Accuracy Posterior Approximation via Random Transport ⋮ Concave-Convex PDMP-based Sampling ⋮ Reversible Jump PDMP Samplers for Variable Selection ⋮ Using Markov transition matrices to generate trial configurations in Markov chain Monte Carlo simulations ⋮ PDMP characterisation of event-chain Monte Carlo algorithms for particle systems ⋮ Unnamed Item ⋮ Piecewise deterministic Markov processes and their invariant measures

Uses Software

• UCI-ml
• Stan
• NUTS

Cites Work

• Unnamed Item
• Unnamed Item
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• Piecewise deterministic simulated annealing
• Lifting Markov chains to speed up mixing
• Sampling-Based Approaches to Calculating Marginal Densities
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods
• Equation of State Calculations by Fast Computing Machines
• Monte Carlo sampling methods using Markov chains and their applications

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