On the Geometric Ergodicity of Hamiltonian Monte Carlo

29 January 2016

Papers citing "On the Geometric Ergodicity of Hamiltonian Monte Carlo"

50 / 65 papers shown

Title
Exponential speed up in Monte Carlo sampling through Radial Updates Johann Ostmeyer 66 2 0 27 Nov 2024
Sacred and Profane: from the Involutive Theory of MCMC to Helpful Hamiltonian Hacks N. Glatt-Holtz Andrew J. Holbrook J. Krometis Cecilia F. Mondaini Ami D. Sheth 28 0 0 22 Oct 2024
Repelling-Attracting Hamiltonian Monte Carlo Siddharth Vishwanath Hyungsuk Tak 16 0 0 07 Mar 2024
Listening to the Noise: Blind Denoising with Gibbs Diffusion David Heurtel-Depeiges C. Margossian Ruben Ohana Bruno Régaldo-Saint Blancard DiffM 35 1 0 29 Feb 2024
Ensemble-Based Annealed Importance Sampling Haoxuan Chen Lexing Ying 33 2 0 28 Jan 2024
Channelling Multimodality Through a Unimodalizing Transport: Warp-U Sampler and Stochastic Bridge Sampling Fei Ding David E. Jones Shiyuan He Xiao-Li Meng OT 17 0 0 01 Jan 2024
Quantifying the effectiveness of linear preconditioning in Markov chain Monte Carlo Max Hird Samuel Livingstone 22 5 0 08 Dec 2023
Learning variational autoencoders via MCMC speed measures Marcel Hirt Vasileios Kreouzis P. Dellaportas BDL DRL 19 2 0 26 Aug 2023
Differentially Private Statistical Inference through $β$ -Divergence One Posterior Sampling Jack Jewson Sahra Ghalebikesabi Chris Holmes 25 2 0 11 Jul 2023
On the convergence of dynamic implementations of Hamiltonian Monte Carlo and No U-Turn Samplers Alain Durmus Samuel Gruffaz Miika Kailas E. Saksman M. Vihola 19 5 0 07 Jul 2023
Geometric Ergodicity in Modified Variations of Riemannian Manifold and Lagrangian Monte Carlo James A. Brofos Vivekananda Roy Roy R. Lederman 11 3 0 04 Jan 2023
Second Order Ensemble Langevin Method for Sampling and Inverse Problems Ziming Liu Andrew M. Stuart Yixuan Wang 24 6 0 09 Aug 2022
Expert Elicitation and Data Noise Learning for Material Flow Analysis using Bayesian Inference Jiayuan Dong Jiankan Liao Xun Huan Daniel R. Cooper 9 6 0 13 Jul 2022
Unbiased Multilevel Monte Carlo methods for intractable distributions: MLMC meets MCMC Guanyang Wang T. Wang 29 14 0 11 Apr 2022
Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms Jeremy Seeman M. Reimherr Aleksandra B. Slavkovic 16 11 0 03 Apr 2022
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 28 25 0 20 Mar 2022
Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte Carlo L. Riou-Durand Jure Vogrinc 15 14 0 26 Feb 2022
Entropy-based adaptive Hamiltonian Monte Carlo Marcel Hirt Michalis K. Titsias P. Dellaportas BDL 29 7 0 27 Oct 2021
Hamiltonian Monte Carlo with Asymmetrical Momentum Distributions Soumyadip Ghosh Ying-Ling Lu Aditya Gopalan 14 3 0 21 Oct 2021
Convergence of position-dependent MALA with application to conditional simulation in GLMMs Vivekananda Roy Lijin Zhang 11 8 0 28 Aug 2021
An Introduction to Hamiltonian Monte Carlo Method for Sampling Nisheeth K. Vishnoi 6 14 0 27 Aug 2021
A Unifying and Canonical Description of Measure-Preserving Diffusions Alessandro Barp So Takao M. Betancourt Alexis Arnaudon Mark Girolami 20 17 0 06 May 2021
Speed Up Zig-Zag G. Vasdekis Gareth O. Roberts 11 11 0 30 Mar 2021
Hamiltonian Monte Carlo in Inverse Problems; Ill-Conditioning and Multi-Modality I. Langmore M. Dikovsky S. Geraedts Peter C. Norgaard R. V. Behren 14 7 0 12 Mar 2021
On $L^q$ Convergence of the Hamiltonian Monte Carlo Soumyadip Ghosh Ying-Ling Lu T. Nowicki 14 1 0 21 Jan 2021
An MCMC Method to Sample from Lattice Distributions Anand George N. Kashyap 12 1 0 16 Jan 2021
Geometric ergodicity of Gibbs samplers for the Horseshoe and its regularized variants S. K. Bhattacharya Kshitij Khare Subhadip Pal 13 7 0 02 Jan 2021
Coupling-based convergence assessment of some Gibbs samplers for high-dimensional Bayesian regression with shrinkage priors N. Biswas A. Bhattacharya Pierre E. Jacob J. Johndrow 12 14 0 09 Dec 2020
Convergence of Preconditioned Hamiltonian Monte Carlo on Hilbert Spaces Jakiw Pidstrigach 12 6 0 17 Nov 2020
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 11 33 0 06 Nov 2020
Geometry-Aware Hamiltonian Variational Auto-Encoder Clément Chadebec Clément Mantoux S. Allassonnière DRL 4 15 0 22 Oct 2020
Magnetic Manifold Hamiltonian Monte Carlo James A. Brofos Roy R. Lederman 6 5 0 15 Oct 2020
Couplings for Andersen Dynamics Nawaf Bou-Rabee A. Eberle 16 11 0 29 Sep 2020
Bayesian modelling of time-varying conditional heteroscedasticity Sayar Karmakar Arkaprava Roy 6 12 0 13 Sep 2020
Non-Canonical Hamiltonian Monte Carlo James A. Brofos Roy R. Lederman 9 6 0 18 Aug 2020
Faster MCMC for Gaussian Latent Position Network Models Neil A. Spencer B. Junker T. Sweet BDL 10 6 0 13 Jun 2020
Mixing Rates for Hamiltonian Monte Carlo Algorithms in Finite and Infinite Dimensions N. Glatt-Holtz Cecilia F. Mondaini 16 10 0 17 Mar 2020
HMC: avoiding rejections by not using leapfrog and some results on the acceptance rate M. Calvo D. Sanz-Alonso J. Sanz-Serna 11 7 0 06 Dec 2019
The Barker proposal: combining robustness and efficiency in gradient-based MCMC Samuel Livingstone Giacomo Zanella 18 48 0 30 Aug 2019
Hug and Hop: a discrete-time, non-reversible Markov chain Monte-Carlo algorithm Matthew Ludkin Chris Sherlock 13 8 0 29 Jul 2019
Monte Carlo simulation on the Stiefel manifold via polar expansion Michael Jauch P. Hoff David B. Dunson 19 30 0 18 Jun 2019
Variational Langevin Hamiltonian Monte Carlo for Distant Multi-modal Sampling Minghao Gu Shiliang Sun BDL 11 0 0 01 Jun 2019
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients Yuansi Chen Raaz Dwivedi Martin J. Wainwright Bin Yu 11 100 0 29 May 2019
Fast Markov chain Monte Carlo for high dimensional Bayesian regression models with shrinkage priors Rui Jin Aixin Tan 19 8 0 16 Mar 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport Matthew Hoffman Pavel Sountsov Joshua V. Dillon I. Langmore Dustin Tran Srinivas Vasudevan BDL 21 103 0 09 Mar 2019
Understanding MCMC Dynamics as Flows on the Wasserstein Space Chang-Shu Liu Jingwei Zhuo Jun Zhu 11 22 0 01 Feb 2019
Stochastic Approximation Hamiltonian Monte Carlo Jonghyun Yun Minsuk Shin Ick Hoon Jin F. Liang 6 4 0 11 Oct 2018
Adaptive Tuning Of Hamiltonian Monte Carlo Within Sequential Monte Carlo Alexander K. Buchholz Nicolas Chopin Pierre E. Jacob 24 32 0 23 Aug 2018
Does Hamiltonian Monte Carlo mix faster than a random walk on multimodal densities? Oren Mangoubi Natesh S. Pillai Aaron Smith 16 31 0 09 Aug 2018
Coupling and Convergence for Hamiltonian Monte Carlo Nawaf Bou-Rabee A. Eberle Raphael Zimmer 77 136 0 01 May 2018