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Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion

27 February 2024

Papers citing "Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion"

41 / 41 papers shown

Title
Improving the evaluation of samplers on multi-modal targets Louis Grenioux Maxence Noble Marylou Gabrié 439 0 0 11 Apr 2025
Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics Omar Chehab Anna Korba Austin Stromme Adrien Vacher 139 4 0 13 Oct 2024
Stochastic Localization via Iterative Posterior Sampling Louis Grenioux Maxence Noble Marylou Gabrié Alain Durmus DiffM 78 16 0 16 Feb 2024
Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo Xunpeng Huang Difan Zou Hanze Dong Yian Ma Tong Zhang DiffM 52 12 0 12 Jan 2024
Nearly $d$ -Linear Convergence Bounds for Diffusion Models via Stochastic Localization Joe Benton Valentin De Bortoli Arnaud Doucet George Deligiannidis DiffM 85 116 0 07 Aug 2023
Reverse Diffusion Monte Carlo Xunpeng Huang Hanze Dong Yi Hao Yi-An Ma Tong Zhang DiffM 72 28 0 05 Jul 2023
Improved sampling via learned diffusions Lorenz Richter Julius Berner DiffM 97 63 0 03 Jul 2023
Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models Gen Li Yuting Wei Yuxin Chen Yuejie Chi DiffM 80 62 0 15 Jun 2023
A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry Yuansi Chen Khashayar Gatmiry 58 6 0 08 Apr 2023
Improved Bound for Mixing Time of Parallel Tempering Holden Lee Zeyu Shen 117 4 0 03 Apr 2023
Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation David Holzmüller Francis R. Bach 78 9 0 06 Mar 2023
Mean-Square Analysis of Discretized Itô Diffusions for Heavy-tailed Sampling Ye He Tyler Farghly Krishnakumar Balasubramanian Murat A. Erdogdu 76 4 0 01 Mar 2023
Denoising Diffusion Samplers Francisco Vargas Will Grathwohl Arnaud Doucet DiffM 61 89 0 27 Feb 2023
Improved dimension dependence of a proximal algorithm for sampling JiaoJiao Fan Bo Yuan Yongxin Chen 74 25 0 20 Feb 2023
Regularized Stein Variational Gradient Flow Ye He Krishnakumar Balasubramanian Bharath K. Sriperumbudur Jianfeng Lu OT 58 12 0 15 Nov 2022
Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions Hongrui Chen Holden Lee Jianfeng Lu DiffM 66 142 0 03 Nov 2022
Convergence of the Inexact Langevin Algorithm and Score-based Generative Models in KL Divergence Kaylee Yingxi Yang Andre Wibisono 77 12 0 02 Nov 2022
Convergence of score-based generative modeling for general data distributions Holden Lee Jianfeng Lu Yixin Tan DiffM 245 137 0 26 Sep 2022
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions Sitan Chen Sinho Chewi Jungshian Li Yuanzhi Li Adil Salim Anru R. Zhang DiffM 217 276 0 22 Sep 2022
Convergence of denoising diffusion models under the manifold hypothesis Valentin De Bortoli DiffM 71 170 0 10 Aug 2022
Localization Schemes: A Framework for Proving Mixing Bounds for Markov Chains Yuansi Chen Ronen Eldan 46 81 0 08 Mar 2022
A Proximal Algorithm for Sampling Jiaming Liang Yongxin Chen 76 18 0 28 Feb 2022
Improved analysis for a proximal algorithm for sampling Yongxin Chen Sinho Chewi Adil Salim Andre Wibisono 100 58 0 13 Feb 2022
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo Krishnakumar Balasubramanian Sinho Chewi Murat A. Erdogdu Adil Salim Matthew Shunshi Zhang 95 65 0 10 Feb 2022
Path Integral Sampler: a stochastic control approach for sampling Qinsheng Zhang Yongxin Chen DiffM 100 117 0 30 Nov 2021
Bayesian Learning via Neural Schrödinger-Föllmer Flows Francisco Vargas Andrius Ovsianas David Fernandes Mark Girolami Neil D. Lawrence Nikolas Nusken BDL 89 49 0 20 Nov 2021
The Mirror Langevin Algorithm Converges with Vanishing Bias Ruilin Li Molei Tao Santosh Vempala Andre Wibisono 88 37 0 24 Sep 2021
Sqrt(d) Dimension Dependence of Langevin Monte Carlo Ruilin Li H. Zha Molei Tao 60 29 0 08 Sep 2021
A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1 Adil Salim Lukang Sun Peter Richtárik 57 20 0 06 Jun 2021
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 353 6,566 0 26 Nov 2020
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 55 35 0 06 Nov 2020
Structured Logconcave Sampling with a Restricted Gaussian Oracle Y. Lee Ruoqi Shen Kevin Tian 56 72 0 07 Oct 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 718 18,310 0 19 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 92 70 0 03 Jun 2020
The Randomized Midpoint Method for Log-Concave Sampling Ruoqi Shen Y. Lee 103 118 0 12 Sep 2019
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices Santosh Vempala Andre Wibisono 90 269 0 20 Mar 2019
On sampling from a log-concave density using kinetic Langevin diffusions A. Dalalyan L. Riou-Durand 75 158 0 24 Jul 2018
Log-concave sampling: Metropolis-Hastings algorithms are fast Raaz Dwivedi Yuansi Chen Martin J. Wainwright Bin Yu 66 255 0 08 Jan 2018
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient A. Dalalyan Avetik G. Karagulyan 75 297 0 29 Sep 2017
Stein Variational Gradient Descent as Gradient Flow Qiang Liu OT 98 277 0 25 Apr 2017
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 312 7,016 0 12 Mar 2015