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Particle Markov chain Monte Carlo methods

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2010-06, Vol.72 (3), p.269-342

2010

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The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method

Journal of the American Statistical Association, 2018-04, Vol.113 (522), p.855-867

2018

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On Particle Methods for Parameter Estimation in State-Space Models

Statistical science, 2015-08, Vol.30 (3), p.328-351

2015

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An adaptive sequential Monte Carlo method for approximate Bayesian computation

Statistics and computing, 2012-09, Vol.22 (5), p.1009-1020

2012

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Non‐reversible parallel tempering: A scalable highly parallel MCMC scheme

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2022-04, Vol.84 (2), p.321-350, Article 321

2022

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Sequential Monte Carlo samplers

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2006-06, Vol.68 (3), p.411-436

2006

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Smoothing algorithms for state–space models

Annals of the Institute of Statistical Mathematics, 2010-02, Vol.62 (1), p.61-89

2010

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On the Utility of Graphics Cards to Perform Massively Parallel Simulation of Advanced Monte Carlo Methods

Journal of computational and graphical statistics, 2010-12, Vol.19 (4), p.769-789

2010

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An Introduction to MCMC for Machine Learning

Machine learning, 2003-01, Vol.50 (1-2), p.5-43

2003

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Inference for Lévy-Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo

Scandinavian journal of statistics, 2011-03, Vol.38 (1), p.1-22

2011

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Monte Carlo Smoothing for Nonlinear Time Series

Journal of the American Statistical Association, 2004-03, Vol.99 (465), p.156-168

2004

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Particle filtering for partially observed Gaussian state space models

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2002-10, Vol.64 (4), p.827-836

2002

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Efficient Block Sampling Strategies for Sequential Monte Carlo Methods

Journal of computational and graphical statistics, 2006-09, Vol.15 (3), p.693-711

2006

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An Adaptive Interacting Wang-Landau Algorithm for Automatic Density Exploration

Journal of computational and graphical statistics, 2013-09, Vol.22 (3), p.749-773

2013

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Simulated likelihood inference for stochastic volatility models using continuous particle filtering

Annals of the Institute of Statistical Mathematics, 2014-06, Vol.66 (3), p.527-552

2014

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Nonreversible Jump Algorithms for Bayesian Nested Model Selection

Journal of computational and graphical statistics, 2020-11, Vol.30 (2), p.312-323

2020

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On Markov chain Monte Carlo methods for tall data

Journal of machine learning research, 2017-05

2017

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Gibbs flow for approximate transport with applications to Bayesian computation

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2021-02, Vol.83 (1), p.156-187

2021

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An adaptive sequential Monte Carlo method for approximate Bayesian computation

Statistics and computing, 2012-09, Vol.22 (5), p.1009-1020

2012

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The correlated pseudomarginal method

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2018-11, Vol.80 (5), p.839-870

2018

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Sequential Monte Carlo methods for diffusion processes

Proceedings of the Royal Society. A, Mathematical, physical, and engineering sciences, 2009-12, Vol.465 (2112), p.3709-3727

2009

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Differentiable samplers for deep latent variable models

Philosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences, 2023-05, Vol.381 (2247)

2023

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On uncertainty quantification in hydrogeology and hydrogeophysics

Advances in water resources, 2017-12, Vol.110, p.166-181

2017

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Network Consensus in the Wasserstein Metric Space of Probability Measures

SIAM journal on control and optimization, 2021-01, Vol.59 (5), p.3261-3277

2021

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Diffusion Schrödinger Bridges for Bayesian Computation

Statistical science, 2024-02, Vol.39 (1), p.90

2024

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Particle Markov chain Monte Carlo methods

The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method

On Particle Methods for Parameter Estimation in State-Space Models

An adaptive sequential Monte Carlo method for approximate Bayesian computation

Non‐reversible parallel tempering: A scalable highly parallel MCMC scheme

Sequential Monte Carlo samplers

Smoothing algorithms for state–space models

On the Utility of Graphics Cards to Perform Massively Parallel Simulation of Advanced Monte Carlo Methods

An Introduction to MCMC for Machine Learning

Inference for Lévy-Driven Stochastic Volatility Models via Adaptive Sequential Monte Carlo

Monte Carlo Smoothing for Nonlinear Time Series

Particle filtering for partially observed Gaussian state space models

Efficient Block Sampling Strategies for Sequential Monte Carlo Methods

An Adaptive Interacting Wang-Landau Algorithm for Automatic Density Exploration

Simulated likelihood inference for stochastic volatility models using continuous particle filtering

Nonreversible Jump Algorithms for Bayesian Nested Model Selection

On Markov chain Monte Carlo methods for tall data

Gibbs flow for approximate transport with applications to Bayesian computation

An adaptive sequential Monte Carlo method for approximate Bayesian computation

The correlated pseudomarginal method

Sequential Monte Carlo methods for diffusion processes

Differentiable samplers for deep latent variable models

On uncertainty quantification in hydrogeology and hydrogeophysics

Network Consensus in the Wasserstein Metric Space of Probability Measures

Diffusion Schrödinger Bridges for Bayesian Computation

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