A Quantum Parallel Markov Chain Monte Carlo

DOI10.1080/10618600.2023.2195890arXiv2112.00212OpenAlexW3217523156MaRDI QIDQ6181412

Andrew J. Holbrook

Publication date: 22 January 2024

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

Full work available at URL: https://arxiv.org/abs/2112.00212

zbMATH Keywords

algorithmsparallel computingMarkov chain Monte Carlo (MCMC)statistical computing

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Optimal scaling for various Metropolis-Hastings algorithms.
• On parallelizable Markov chain Monte Carlo algorithms with waste-recycling
• Inference from iterative simulation using multiple sequences
• Quantum circuits for floating-point arithmetic
• Scalable Bayesian inference for self-excitatory stochastic processes applied to big American gunfire data
• Generating MCMC proposals by randomly rotating the regular simplex
• Bayesian mitigation of spatial coarsening for a Hawkes model applied to gunfire, wildfire and viral contagion
• A multiple-try Metropolis-Hastings algorithm with tailored proposals
• Sequential Monte Carlo Methods in Practice
• ggplot2
• Quantum Computation and Quantum Information
• Quantum Random Access Memory
• Does Waste Recycling Really Improve the Multi-Proposal Metropolis–Hastings algorithm? an Analysis Based on Control Variates
• Strengths and Weaknesses of Quantum Computing
• On Estimation of Covariance Matrices With Kronecker Product Structure
• Massive Parallelization Boosts Big Bayesian Multidimensional Scaling
• Equation of State Calculations by Fast Computing Machines
• Quantum speedup of Monte Carlo methods
• Monte Carlo sampling methods using Markov chains and their applications

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