Piecewise Deterministic Markov Processes for Continuous-Time Monte Carlo

23 November 2016

Papers citing "Piecewise Deterministic Markov Processes for Continuous-Time Monte Carlo"

50 / 68 papers shown

Title
Numerical Generalized Randomized Hamiltonian Monte Carlo for piecewise smooth target densities Jimmy Huy Tran T. S. Kleppe BDL 69 0 0 25 Apr 2025
$Fused $L_{1/2}$ prior for large scale linear inverse problem with Gibbs bouncy particle sampler$ Fused $L_{1/2}$ prior for large scale linear inverse problem with Gibbs bouncy particle sampler Xiongwen Ke Yanan Fan Qingping Zhou 49 0 0 12 Sep 2024
Piecewise deterministic generative models Andrea Bertazzi Alain Durmus Dario Shariatian Umut Simsekli Éric Moulines DiffM 58 1 0 28 Jul 2024
Stochastic Gradient Piecewise Deterministic Monte Carlo Samplers Paul Fearnhead Sebastiano Grazzi Chris Nemeth Gareth O. Roberts 75 0 0 27 Jun 2024
Hoeffding's inequality for continuous-time Markov chains Jinpeng Liu Yuanyuan Liu Lin Zhou 50 0 0 23 Apr 2024
Tuning diagonal scale matrices for HMC Jimmy Huy Tran T. S. Kleppe 70 4 0 12 Mar 2024
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples Leo L. Duan Anirban Bhattacharya 98 1 0 25 Jan 2024
Numerical Generalized Randomized HMC processes for restricted domains T. S. Kleppe R. Liesenfeld 41 2 0 24 Nov 2023
Causal structure learning with momentum: Sampling distributions over Markov Equivalence Classes of DAGs Moritz Schauer Marcel Wienöbst CML 90 2 0 09 Oct 2023
Debiasing Piecewise Deterministic Markov Process samplers using couplings Adrien Corenflos Matthew Sutton Nicolas Chopin 54 1 0 27 Jun 2023
Piecewise Deterministic Markov Processes for Bayesian Neural Networks Ethan Goan Dimitri Perrin Kerrie Mengersen Clinton Fookes 67 0 0 17 Feb 2023
Pigeonhole Stochastic Gradient Langevin Dynamics for Large Crossed Mixed Effects Models Xinyu Zhang Cheng Li 69 0 0 18 Dec 2022
Log-density gradient covariance and automatic metric tensors for Riemann manifold Monte Carlo methods T. S. Kleppe 74 3 0 03 Nov 2022
On free energy barriers in Gaussian priors and failure of cold start MCMC for high-dimensional unimodal distributions Afonso S. Bandeira Antoine Maillard Richard Nickl Sven Wang 83 10 0 05 Sep 2022
Sampling algorithms in statistical physics: a guide for statistics and machine learning Michael F Faulkner Samuel Livingstone 57 7 0 09 Aug 2022
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 100 16 0 01 Aug 2022
Automatic Zig-Zag sampling in practice Alice Corbella S. Spencer Gareth O. Roberts 67 20 0 22 Jun 2022
Stereographic Markov Chain Monte Carlo Jun Yang K. Latuszyñski Gareth O. Roberts 82 14 0 24 May 2022
Continuously-Tempered PDMP Samplers Matthew Sutton R. Salomone Augustin Chevallier Paul Fearnhead 58 1 0 19 May 2022
Efficient computation of the volume of a polytope in high-dimensions using Piecewise Deterministic Markov Processes Augustin Chevallier F. Cazals Paul Fearnhead 46 13 0 18 Feb 2022
Accelerating Bayesian inference of dependency between complex biological traits Zhenyu Zhang A. Nishimura Nídia S. Trovão Joshua L. Cherry Andrew J Holbrook Xiang Ji P. Lemey M. Suchard 41 2 0 18 Jan 2022
Optimal design of the Barker proposal and other locally-balanced Metropolis-Hastings algorithms Jure Vogrinc Samuel Livingstone Giacomo Zanella 47 11 0 04 Jan 2022
Strong Invariance Principles for Ergodic Markov Processes A. Pengel J. Bierkens 39 1 0 24 Nov 2021
The Application of Zig-Zag Sampler in Sequential Markov Chain Monte Carlo Yu Han Kazuyuki Nakamura 50 2 0 18 Nov 2021
PDMP Monte Carlo methods for piecewise-smooth densities Augustin Chevallier Samuel Power Andi Q. Wang Paul Fearnhead 56 11 0 10 Nov 2021
Non-reversible processes: GENERIC, Hypocoercivity and fluctuations M. H. Duong M. Ottobre 43 7 0 30 Oct 2021
Asynchronous and Distributed Data Augmentation for Massive Data Settings Jiayuan Zhou Kshitij Khare Sanvesh Srivastava 63 3 0 18 Sep 2021
A Note on the Polynomial Ergodicity of the One-Dimensional Zig-Zag process G. Vasdekis Gareth O. Roberts 74 6 0 21 Jun 2021
Divide-and-Conquer Bayesian Inference in Hidden Markov Models Chunlei Wang Sanvesh Srivastava 61 9 0 30 May 2021
Dimension-free Mixing for High-dimensional Bayesian Variable Selection Quan Zhou Jun Yang Dootika Vats Gareth O. Roberts Jeffrey S. Rosenthal 59 26 0 12 May 2021
Speed Up Zig-Zag G. Vasdekis Gareth O. Roberts 52 11 0 30 Mar 2021
Adaptive schemes for piecewise deterministic Monte Carlo algorithms Andrea Bertazzi J. Bierkens 46 10 0 27 Dec 2020
Ultimate Pólya Gamma Samplers -- Efficient MCMC for possibly imbalanced binary and categorical data Gregor Zens Sylvia Fruhwirth-Schnatter Helga Wagner SyDa 108 13 0 13 Nov 2020
No Free Lunch for Approximate MCMC J. Johndrow Natesh S. Pillai Aaron Smith 104 18 0 23 Oct 2020
Reversible Jump PDMP Samplers for Variable Selection Augustin Chevallier Paul Fearnhead Matthew Sutton 65 18 0 22 Oct 2020
On explicit $L^2$ -convergence rate estimate for piecewise deterministic Markov processes in MCMC algorithms Jianfeng Lu Lihan Wang 76 27 0 29 Jul 2020
The Boomerang Sampler J. Bierkens Sebastiano Grazzi K. Kamatani Gareth O. Roberts 47 32 0 24 Jun 2020
Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with State-Dependent Event Rates T. S. Kleppe 54 12 0 04 May 2020
Zig-zag sampling for discrete structures and non-reversible phylogenetic MCMC Jere Koskela 60 7 0 19 Apr 2020
Analysis of Stochastic Gradient Descent in Continuous Time J. Latz 81 41 0 15 Apr 2020
Computing Bayes: Bayesian Computation from 1763 to the 21st Century G. Martin David T. Frazier Christian P. Robert 95 17 0 14 Apr 2020
Posterior computation with the Gibbs zig-zag sampler Matthias Sachs Deborshee Sen Jianfeng Lu David B. Dunson 89 7 0 08 Apr 2020
Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains M. Peruzzi Sudipto Banerjee Andrew O. Finley 74 55 0 25 Mar 2020
A piecewise deterministic Monte Carlo method for diffusion bridges J. Bierkens Sebastiano Grazzi Frank van der Meulen Moritz Schauer DiffM 83 22 0 16 Jan 2020
Large deviations for the empirical measure of the zig-zag process J. Bierkens Pierre Nyquist Mikola C. Schlottke 24 10 0 13 Dec 2019
Parallelising MCMC via Random Forests Changye Wu Christian P. Robert 18 5 0 21 Nov 2019
Cores for Piecewise-Deterministic Markov Processes used in Markov Chain Monte Carlo P. Holderrieth 93 10 0 20 Oct 2019
Collective Proposal Distributions for Nonlinear MCMC samplers: Mean-Field Theory and Fast Implementation Grégoire Clarté A. Diez Jean Feydy 71 8 0 18 Sep 2019
The Barker proposal: combining robustness and efficiency in gradient-based MCMC Samuel Livingstone Giacomo Zanella 88 50 0 30 Aug 2019
Hug and Hop: a discrete-time, non-reversible Markov chain Monte-Carlo algorithm Matthew Ludkin Chris Sherlock 54 8 0 29 Jul 2019