{"cited_by_count":715708,"description":"This cluster of papers focuses on the application of Bayesian Monte Carlo methods, such as Markov Chain Monte Carlo (MCMC), Approximate Bayesian Computation, and Hamiltonian Monte Carlo, in scientific inference for inverse problems, model selection, and statistical estimation. It also explores adaptive MCMC algorithms and stochastic gradient Langevin dynamics for efficient parameter inference and approximation algorithms.","display_name":"Markov Chains and Monte Carlo Methods","domain_id":"3","external_ids":{"openalex":"https://openalex.org/T12056","wikipedia":"https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo"},"field_id":"26","id":"T12056","keywords":[{"display_name":"Markov chain Monte Carlo","id":"markov-chain-monte-carlo","score":0.2674,"url":"https://openalex.org/keywords/markov-chain-monte-carlo"},{"display_name":"sequential Monte Carlo","id":"sequential-monte-carlo","score":0.2862,"url":"https://openalex.org/keywords/sequential-monte-carlo"},{"display_name":"Metropolis-Hastings algorithm","id":"metropolis-hastings-algorithm","score":0.3539,"url":"https://openalex.org/keywords/metropolis-hastings-algorithm"},{"display_name":"approximate Bayesian computation","id":"approximate-bayesian-computation","score":0.3025,"url":"https://openalex.org/keywords/approximate-bayesian-computation"},{"display_name":"Hamiltonian Monte Carlo","id":"hamiltonian-monte-carlo","score":0.2973,"url":"https://openalex.org/keywords/hamiltonian-monte-carlo"},{"display_name":"simulation-based inference","id":"simulation-based-inference","score":0.3094,"url":"https://openalex.org/keywords/simulation-based-inference"},{"display_name":"posterior sampling","id":"posterior-sampling","score":0.3214,"url":"https://openalex.org/keywords/posterior-sampling"},{"display_name":"rejection sampling","id":"rejection-sampling","score":0.2204,"url":"https://openalex.org/keywords/rejection-sampling"},{"display_name":"high-dimensional sampling","id":"high-dimensional-sampling","score":0.7061,"url":"https://openalex.org/keywords/high-dimensional-sampling"},{"display_name":"sampling algorithms","id":"sampling-algorithms","score":0.232,"url":"https://openalex.org/keywords/sampling-algorithms"},{"display_name":"Markov chain convergence","id":"markov-chain-convergence","score":0.3591,"url":"https://openalex.org/keywords/markov-chain-convergence"},{"display_name":"posterior approximation","id":"posterior-approximation","score":0.2351,"url":"https://openalex.org/keywords/posterior-approximation"},{"display_name":"intractable likelihood","id":"intractable-likelihood","score":0.7406,"url":"https://openalex.org/keywords/intractable-likelihood"},{"display_name":"Metropolis algorithm","id":"metropolis-algorithm","score":0.206,"url":"https://openalex.org/keywords/metropolis-algorithm"},{"display_name":"reversible jump MCMC","id":"reversible-jump-mcmc","score":0.3172,"url":"https://openalex.org/keywords/reversible-jump-mcmc"},{"display_name":"geometric ergodicity","id":"geometric-ergodicity","score":0.3815,"url":"https://openalex.org/keywords/geometric-ergodicity"},{"display_name":"reversible Markov chains","id":"reversible-markov-chains","score":0.3606,"url":"https://openalex.org/keywords/reversible-markov-chains"},{"display_name":"nested sampling","id":"nested-sampling","score":0.2207,"url":"https://openalex.org/keywords/nested-sampling"},{"display_name":"proposal distribution","id":"proposal-distribution","score":0.3199,"url":"https://openalex.org/keywords/proposal-distribution"},{"display_name":"adaptive MCMC","id":"adaptive-mcmc","score":0.7482,"url":"https://openalex.org/keywords/adaptive-mcmc"},{"display_name":"normalizing constants","id":"normalizing-constants","score":0.2193,"url":"https://openalex.org/keywords/normalizing-constants"},{"display_name":"adaptive importance sampling","id":"adaptive-importance-sampling","score":0.3226,"url":"https://openalex.org/keywords/adaptive-importance-sampling"},{"display_name":"effective sample size","id":"effective-sample-size","score":0.2019,"url":"https://openalex.org/keywords/effective-sample-size"},{"display_name":"perfect sampling","id":"perfect-sampling","score":0.5488,"url":"https://openalex.org/keywords/perfect-sampling"},{"display_name":"Bayesian computation","id":"bayesian-computation","score":0.46,"url":"https://openalex.org/keywords/bayesian-computation"}],"legacy_keywords":["Bayesian Monte Carlo","Markov Chain","Approximate Bayesian Computation","Adaptive MCMC","Hamiltonian Monte Carlo","Stochastic Gradient Langevin Dynamics","Inverse Problems","Model Selection","Statistical Inference","Approximation Algorithms"],"openalex_id":"https://openalex.org/T12056","source_created_date":"2024-01-23T15:27:12","source_updated_date":"2026-10-17T03:02:00","subfield_id":"2613","url":"/topics/T12056","works_api_url":"https://api.openalex.org/works?filter=topics.id:T12056","works_count":29936,"label":"Markov Chains and Monte Carlo Methods","provider":"openalex","revision":"a4104d8b6cfef3ab","taxonomy_revision":"f050b5d4780b1289","title":"Markov Chains and Monte Carlo Methods","kind":"topic-directory","aeo_cohort":"topic-directory","catalogue_revision":"f050b5d4780b1289","numeric_address":"36249558343132213","address_version":"morton4x16-v1","coordinates":[3,26,2613,12056],"answer_status":"Directory metadata; local answer requires separate source review","truth_status":"Subject descriptor, not a factual answer or a demonstrated knowledge gap","reviewed_answer":null}