Underdamped Langevin MCMC: A non-asymptotic analysis

12 July 2017

Niladri S. Chatterji

Papers citing "Underdamped Langevin MCMC: A non-asymptotic analysis"

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Title
On the query complexity of sampling from non-log-concave distributions Yuchen He Chihao Zhang 41 0 0 10 Feb 2025
Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance Marta Gentiloni-Silveri Antonio Ocello 33 2 0 04 Jan 2025
Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics Daniel Paulin P. Whalley Neil K. Chada B. Leimkuhler BDL 41 4 0 14 Oct 2024
A General Continuous-Time Formulation of Stochastic ADMM and Its Variants Chris Junchi Li 18 0 0 22 Apr 2024
Mean-field underdamped Langevin dynamics and its spacetime discretization Qiang Fu Ashia Wilson 32 4 0 26 Dec 2023
Accelerating optimization over the space of probability measures Shi Chen Wenxuan Wu Yuhang Yao Stephen J. Wright 18 4 0 06 Oct 2023
Moreau-Yoshida Variational Transport: A General Framework For Solving Regularized Distributional Optimization Problems Dai Hai Nguyen Tetsuya Sakurai 14 1 0 31 Jul 2023
Contraction Rate Estimates of Stochastic Gradient Kinetic Langevin Integrators B. Leimkuhler Daniel Paulin P. Whalley 23 5 0 14 Jun 2023
Solving Linear Inverse Problems using Higher-Order Annealed Langevin Diffusion Nicolas Zilberstein A. Sabharwal Santiago Segarra DiffM 39 7 0 08 May 2023
Query lower bounds for log-concave sampling Sinho Chewi Jaume de Dios Pont Jerry Li Chen Lu Shyam Narayanan 27 8 0 05 Apr 2023
Contraction and Convergence Rates for Discretized Kinetic Langevin Dynamics B. Leimkuhler Daniel Paulin P. Whalley 32 16 0 21 Feb 2023
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler Sivakanth Gopi Y. Lee Daogao Liu Ruoqi Shen Kevin Tian 17 7 0 13 Feb 2023
Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity -- the Strongly Convex Case Tim Johnston Iosif Lytras Sotirios Sabanis 25 8 0 19 Jan 2023
Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration Nawaf Bou-Rabee Milo Marsden 26 12 0 20 Nov 2022
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling Jason M. Altschuler Kunal Talwar 27 24 0 16 Oct 2022
Condition-number-independent convergence rate of Riemannian Hamiltonian Monte Carlo with numerical integrators Yunbum Kook Y. Lee Ruoqi Shen Santosh Vempala 30 12 0 13 Oct 2022
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants Andrew M. Childs Tongyang Li Jin-Peng Liu C. Wang Ruizhe Zhang 20 16 0 12 Oct 2022
Fisher information lower bounds for sampling Sinho Chewi P. Gerber Holden Lee Chen Lu 43 15 0 05 Oct 2022
Gradient Norm Minimization of Nesterov Acceleration: $o(1/k^3)$ Shu Chen Bin Shi Ya-xiang Yuan 23 15 0 19 Sep 2022
Nesterov smoothing for sampling without smoothness JiaoJiao Fan Bo Yuan Jiaming Liang Yongxin Chen 32 2 0 15 Aug 2022
Unbiased Estimation using Underdamped Langevin Dynamics Hamza Ruzayqat Neil K. Chada Ajay Jasra 29 4 0 14 Jun 2022
Convergence for score-based generative modeling with polynomial complexity Holden Lee Jianfeng Lu Yixin Tan DiffM 16 126 0 13 Jun 2022
Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte Carlo L. Riou-Durand Jure Vogrinc 15 14 0 26 Feb 2022
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space Yunbum Kook Y. Lee Ruoqi Shen Santosh Vempala 11 38 0 03 Feb 2022
HMC and underdamped Langevin united in the unadjusted convex smooth case Nicolai Gouraud Pierre Le Bris Adrien Majka Pierre Monmarché 15 10 0 02 Feb 2022
A Kernel-Expanded Stochastic Neural Network Y. Sun F. Liang 15 5 0 14 Jan 2022
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi-An Ma Zhao-quan Song Guang Lin FedML 20 16 0 09 Dec 2021
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel Yindong Chen Yiwei Wang Lulu Kang Chun Liu 13 1 0 21 Nov 2021
A Proximal Algorithm for Sampling from Non-smooth Potentials Jiaming Liang Yongxin Chen 29 26 0 09 Oct 2021
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint Y. Freund Yi-An Ma Tong Zhang 27 16 0 05 Oct 2021
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension Alain Durmus A. Eberle 22 19 0 02 Aug 2021
Uniform minorization condition and convergence bounds for discretizations of kinetic Langevin dynamics Alain Durmus Aurélien Enfroy Eric Moulines G. Stoltz 17 17 0 30 Jul 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
Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie R. Laumont Valentin De Bortoli Andrés Almansa J. Delon Alain Durmus Marcelo Pereyra 16 109 0 08 Mar 2021
The shifted ODE method for underdamped Langevin MCMC James Foster Terry Lyons Harald Oberhauser 11 16 0 10 Jan 2021
Random Coordinate Underdamped Langevin Monte Carlo Zhiyan Ding Qin Li Jianfeng Lu Stephen J. Wright BDL 11 13 0 22 Oct 2020
Random Coordinate Langevin Monte Carlo Zhiyan Ding Qin Li Jianfeng Lu Stephen J. Wright BDL 8 11 0 03 Oct 2020
Unnormalized Variational Bayes Saeed Saremi BDL 81 1 0 29 Jul 2020
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias Lu Yu Krishnakumar Balasubramanian S. Volgushev Murat A. Erdogdu 19 50 0 14 Jun 2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence Sinho Chewi Thibaut Le Gouic Chen Lu Tyler Maunu Philippe Rigollet 18 66 0 03 Jun 2020
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization Ömer Deniz Akyildiz Sotirios Sabanis 35 17 0 13 Feb 2020
Wasserstein Control of Mirror Langevin Monte Carlo Kelvin Shuangjian Zhang Gabriel Peyré M. Fadili Marcelo Pereyra 11 65 0 11 Feb 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo Y. Lee Ruoqi Shen Kevin Tian 17 37 0 10 Feb 2020
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 16 135 0 16 Jul 2019
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting Maxime Vono Daniel Paulin Arnaud Doucet 8 37 0 23 May 2019
Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning Huy N. Chau M. Rásonyi 17 10 0 25 Mar 2019
Accelerated Flow for Probability Distributions Amirhossein Taghvaei P. Mehta 21 30 0 10 Jan 2019
On sampling from a log-concave density using kinetic Langevin diffusions A. Dalalyan L. Riou-Durand 11 155 0 24 Jul 2018
Markov Chain Importance Sampling -- a highly efficient estimator for MCMC Ingmar Schuster I. Klebanov 17 24 0 18 May 2018
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem Andre Wibisono 13 177 0 22 Feb 2018