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High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm

28 August 2019

Papers citing "High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm"

50 / 51 papers shown

Title
Sequential Monte Carlo approximations of Wasserstein--Fisher--Rao gradient flows Francesca R. Crucinio Sahani Pathiraja 50 0 0 06 Jun 2025
Accelerating Langevin Monte Carlo Sampling: A Large Deviations Analysis Nian Yao Pervez Ali Xihua Tao Lingjiong Zhu 75 1 0 24 Mar 2025
Underdamped Diffusion Bridges with Applications to Sampling Denis Blessing Julius Berner Lorenz Richter Gerhard Neumann DiffM 138 6 0 02 Mar 2025
Generative Modelling with High-Order Langevin Dynamics Ziqiang Shi Rujie Liu DiffM 122 2 0 03 Jan 2025
Feynman-Kac Operator Expectation Estimator Jingyuan Li Wei Liu 81 0 0 02 Jul 2024
Faster Sampling via Stochastic Gradient Proximal Sampler Xunpeng Huang Difan Zou Yian Ma Hanze Dong Tong Zhang 96 3 0 27 May 2024
A connection between Tempering and Entropic Mirror Descent Nicolas Chopin F. R. Crucinio Anna Korba 65 14 0 18 Oct 2023
On the Posterior Distribution in Denoising: Application to Uncertainty Quantification Hila Manor T. Michaeli UQCV 120 17 0 24 Sep 2023
A Gentle Introduction to Gradient-Based Optimization and Variational Inequalities for Machine Learning Neha S. Wadia Yatin Dandi Michael I. Jordan AI4CE 92 0 0 09 Sep 2023
Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling Teresa Klatzer P. Dobson Y. Altmann Marcelo Pereyra J. Sanz-Serna K. Zygalakis 64 5 0 18 Aug 2023
Reverse Diffusion Monte Carlo Xunpeng Huang Hanze Dong Yi Hao Yi-An Ma Tong Zhang DiffM 115 28 0 05 Jul 2023
Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited Lu Yu Avetik G. Karagulyan A. Dalalyan 67 7 0 14 Jun 2023
Chain of Log-Concave Markov Chains Saeed Saremi Ji Won Park Francis R. Bach 54 7 0 31 May 2023
Solving Linear Inverse Problems using Higher-Order Annealed Langevin Diffusion Nicolas Zilberstein A. Sabharwal Santiago Segarra DiffM 96 9 0 08 May 2023
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm? Yuansi Chen Khashayar Gatmiry 129 16 0 10 Apr 2023
Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusions Raghav Singhal Mark Goldstein Rajesh Ranganath DiffM 71 22 0 14 Feb 2023
Hamiltonian Monte Carlo for efficient Gaussian sampling: long and random steps Simon Apers S. Gribling Dániel Szilágyi 86 10 0 26 Sep 2022
Learning and Inference in Sparse Coding Models with Langevin Dynamics Michael Y.-S. Fang M. Mudigonda Ryan Zarcone A. Khosrowshahi Bruno A. Olshausen SyDa 74 4 0 23 Apr 2022
Private Convex Optimization via Exponential Mechanism Sivakanth Gopi Y. Lee Daogao Liu 141 54 0 01 Mar 2022
Heavy-tailed denoising score matching J. Deasy Nikola Simidjievski Pietro Lio DiffM 78 16 0 17 Dec 2021
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion Tim Dockhorn Arash Vahdat Karsten Kreis DiffM 110 237 0 14 Dec 2021
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi-An Ma Zhao Song Guang Lin FedML 82 17 0 09 Dec 2021
Optimal friction matrix for underdamped Langevin sampling Martin Chak N. Kantas T. Lelièvre G. Pavliotis 54 9 0 30 Nov 2021
Estimating High Order Gradients of the Data Distribution by Denoising Chenlin Meng Yang Song Wenzhe Li Stefano Ermon DiffM 85 46 0 08 Nov 2021
De-randomizing MCMC dynamics with the diffusion Stein operator Zheyan Shen Markus Heinonen Samuel Kaski DiffM 34 4 0 07 Oct 2021
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint Y. Freund Yi-An Ma Tong Zhang 72 16 0 05 Oct 2021
Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling Keru Wu S. Schmidler Yuansi Chen 127 54 0 27 Sep 2021
Sqrt(d) Dimension Dependence of Langevin Monte Carlo Ruilin Li H. Zha Molei Tao 94 29 0 08 Sep 2021
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions Y. Lee Ruoqi Shen Kevin Tian 54 20 0 10 Jun 2021
Quantifying the mini-batching error in Bayesian inference for Adaptive Langevin dynamics Inass Sekkat G. Stoltz 47 4 0 21 May 2021
Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations J. Sanz-Serna K. Zygalakis 71 23 0 26 Apr 2021
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm Sinho Chewi Chen Lu Kwangjun Ahn Xiang Cheng Thibaut Le Gouic Philippe Rigollet 105 66 0 23 Dec 2020
Complexity of zigzag sampling algorithm for strongly log-concave distributions Jianfeng Lu Lihan Wang 62 6 0 21 Dec 2020
Efficient Numerical Algorithms for the Generalized Langevin Equation Benedict Leimkuhler Matthias Sachs 13 13 0 08 Dec 2020
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 66 35 0 06 Nov 2020
Structured Logconcave Sampling with a Restricted Gaussian Oracle Y. Lee Ruoqi Shen Kevin Tian 79 73 0 07 Oct 2020
Quasi-symplectic Langevin Variational Autoencoder Zihao Wang H. Delingette BDL DRL 73 4 0 02 Sep 2020
Active Importance Sampling for Variational Objectives Dominated by Rare Events: Consequences for Optimization and Generalization Grant M. Rotskoff Andrew R. Mitchell Eric Vanden-Eijnden 51 13 0 11 Aug 2020
Langevin Monte Carlo: random coordinate descent and variance reduction Zhiyan Ding Qin Li BDL 52 12 0 26 Jul 2020
A Decentralized Approach to Bayesian Learning Anjaly Parayil H. Bai Jemin George Prudhvi K. Gurram 29 2 0 14 Jul 2020
Projection Robust Wasserstein Distance and Riemannian Optimization Tianyi Lin Chenyou Fan Nhat Ho Marco Cuturi Michael I. Jordan 88 69 0 12 Jun 2020
Variance reduction for Random Coordinate Descent-Langevin Monte Carlo Zhiyan Ding Qin Li BDL 42 0 0 10 Jun 2020
Composite Logconcave Sampling with a Restricted Gaussian Oracle Ruoqi Shen Kevin Tian Y. Lee 66 10 0 10 Jun 2020
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness Murat A. Erdogdu Rasa Hosseinzadeh 88 77 0 27 May 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo Y. Lee Ruoqi Shen Kevin Tian 81 37 0 10 Feb 2020
Bayesian interpretation of SGD as Ito process Soma Yokoi Issei Sato 38 5 0 20 Nov 2019
Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry Andre Wibisono 140 49 0 04 Nov 2019
The Randomized Midpoint Method for Log-Concave Sampling Ruoqi Shen Y. Lee 125 118 0 12 Sep 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond Xuechen Li Denny Wu Lester W. Mackey Murat A. Erdogdu 93 71 0 19 Jun 2019
Optimal Convergence Rate of Hamiltonian Monte Carlo for Strongly Logconcave Distributions Zongchen Chen Santosh Vempala 82 65 0 07 May 2019