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Information-geometric Markov Chain Monte Carlo methods using Diffusions

31 March 2014

Papers citing "Information-geometric Markov Chain Monte Carlo methods using Diffusions"

21 / 21 papers shown

Title
Measure transport with kernel mean embeddings Linfeng Wang Nikolas Nusken 62 8 0 23 Jan 2024
Quantifying the effectiveness of linear preconditioning in Markov chain Monte Carlo Max Hird Samuel Livingstone 65 5 0 08 Dec 2023
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms Tim Tsz-Kit Lau Han Liu Thomas Pock 97 4 0 25 May 2023
Transport map unadjusted Langevin algorithms: learning and discretizing perturbed samplers Benjamin J. Zhang Youssef M. Marzouk K. Spiliopoulos 78 0 0 14 Feb 2023
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents Alessandro Barp Lancelot Da Costa G. Francca Karl J. Friston Mark Girolami Michael I. Jordan G. Pavliotis 97 25 0 20 Mar 2022
Geometrically adapted Langevin dynamics for Markov chain Monte Carlo simulations Mariya Mamajiwala D. Roy S. Guillas 22 0 0 20 Jan 2022
The Application of Zig-Zag Sampler in Sequential Markov Chain Monte Carlo Yu Han Kazuyuki Nakamura 44 2 0 18 Nov 2021
Convergence of position-dependent MALA with application to conditional simulation in GLMMs Vivekananda Roy Lijin Zhang 56 8 0 28 Aug 2021
Geometry-informed irreversible perturbations for accelerated convergence of Langevin dynamics Benjamin J. Zhang Youssef M. Marzouk K. Spiliopoulos 36 8 0 18 Aug 2021
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 72 17 0 06 May 2021
A fresh take on 'Barker dynamics' for MCMC Max Hird Samuel Livingstone Giacomo Zanella 93 9 0 17 Dec 2020
Quasi-symplectic Langevin Variational Autoencoder Zihao Wang H. Delingette BDL DRL 73 4 0 02 Sep 2020
$Gradients do grow on trees: a linear-time ${\cal O}\hspace{-0.2em}\left( N \right)$-dimensional gradient for statistical phylogenetics$ Gradients do grow on trees: a linear-time ${\cal O}\hspace{-0.2em}\left( N \right)$ -dimensional gradient for statistical phylogenetics X. Ji Zhenyu Zhang Andrew J Holbrook A. Nishimura G. Baele A. Rambaut P. Lemey M. Suchard 35 31 0 29 May 2019
Geometry and Dynamics for Markov Chain Monte Carlo Alessandro Barp François‐Xavier Briol A. Kennedy Mark Girolami AI4CE 70 31 0 08 May 2017
Geometric adaptive Monte Carlo in random environment Theodore Papamarkou Alexey Lindo E. Ford 19 4 0 29 Aug 2016
On the Geometric Ergodicity of Hamiltonian Monte Carlo Samuel Livingstone M. Betancourt Simon Byrne Mark Girolami 133 117 0 29 Jan 2016
Asymptotic Analysis of the Random-Walk Metropolis Algorithm on Ridged Densities A. Beskos Gareth O. Roberts Alexandre Hoang Thiery Natesh Pillai OT 54 15 0 09 Oct 2015
Geometric ergodicity of the Random Walk Metropolis with position-dependent proposal covariance Samuel Livingstone 169 11 0 21 Jul 2015
Langevin and Hamiltonian based Sequential MCMC for Efficient Bayesian Filtering in High-dimensional Spaces F. Septier G. Peters 94 58 0 22 Apr 2015
Adaptive step size selection for Hessian-based manifold Langevin samplers T. S. Kleppe 55 14 0 29 Jan 2015
Consistency and fluctuations for stochastic gradient Langevin dynamics Yee Whye Teh Alexandre Hoang Thiery Sebastian J. Vollmer 116 235 0 01 Sep 2014