Error Bounds for Flow Matching Methods

26 May 2023

George Deligiannidis

Papers citing "Error Bounds for Flow Matching Methods"

25 / 25 papers shown

Title
Local Flow Matching Generative Models Chen Xu Xiuyuan Cheng Yao Xie 49 1 0 03 Jan 2025
Path-Guided Particle-based Sampling Mingzhou Fan Ruida Zhou C. Tian Xiaoning Qian 92 5 0 04 Dec 2024
How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces? Weiguo Gao Ming Li OOD 50 2 0 31 Oct 2024
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework Yinuo Ren Haoxuan Chen Grant M. Rotskoff Lexing Ying 52 3 0 04 Oct 2024
PnP-Flow: Plug-and-Play Image Restoration with Flow Matching Ségolène Martin Anne Gagneux Paul Hagemann Gabriele Steidl 51 9 0 03 Oct 2024
Theoretical guarantees in KL for Diffusion Flow Matching Marta Gentiloni Silveri Giovanni Conforti Alain Durmus 53 2 0 12 Sep 2024
A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models Gen Li Yuting Wei Yuejie Chi Yuxin Chen DiffM 47 22 0 05 Aug 2024
Accelerating Convergence of Score-Based Diffusion Models, Provably Gen Li Yu Huang Timofey Efimov Yuting Wei Yuejie Chi Yuxin Chen DiffM 61 29 0 06 Mar 2024
Critical windows: non-asymptotic theory for feature emergence in diffusion models Marvin Li Sitan Chen DiffM 50 11 0 03 Mar 2024
Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial Wenpin Tang Hanyang Zhao DiffM 58 24 0 12 Feb 2024
Contractive Diffusion Probabilistic Models Wenpin Tang Hanyang Zhao DiffM 59 13 0 23 Jan 2024
SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers Nanye Ma Mark Goldstein M. S. Albergo Nicholas M. Boffi Eric Vanden-Eijnden Saining Xie DiffM 48 171 0 16 Jan 2024
A Good Score Does not Lead to A Good Generative Model Sixu Li Shi Chen Qin Li DiffM 79 15 0 10 Jan 2024
Conditional Stochastic Interpolation for Generative Learning Ding Huang Jian Huang Ting Li Guohao Shen BDL DiffM 43 4 0 09 Dec 2023
Gaussian Interpolation Flows Yuan Gao Jianxia Huang Yuling Jiao AI4CE 30 2 0 20 Nov 2023
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space Xiuyuan Cheng Jianfeng Lu Yixin Tan Yao Xie 116 15 0 26 Oct 2023
Analysis of learning a flow-based generative model from limited sample complexity Hugo Cui Florent Krzakala Eric Vanden-Eijnden Lenka Zdeborová DRL 49 17 0 05 Oct 2023
Nearly $d$ -Linear Convergence Bounds for Diffusion Models via Stochastic Localization Joe Benton Valentin De Bortoli Arnaud Doucet George Deligiannidis DiffM 54 103 0 07 Aug 2023
Learning Mixtures of Gaussians Using the DDPM Objective Kulin Shah Sitan Chen Adam R. Klivans DiffM 46 38 0 03 Jul 2023
The probability flow ODE is provably fast Sitan Chen Sinho Chewi Holden Lee Yuanzhi Li Jianfeng Lu Adil Salim DiffM 43 84 0 19 May 2023
Stochastic Interpolants: A Unifying Framework for Flows and Diffusions M. S. Albergo Nicholas M. Boffi Eric Vanden-Eijnden DiffM 257 271 0 15 Mar 2023
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models Louis Sharrock J. Simons Song Liu Mark Beaumont DiffM 64 34 0 10 Oct 2022
Convergence of score-based generative modeling for general data distributions Holden Lee Jianfeng Lu Yixin Tan DiffM 191 129 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 135 249 0 22 Sep 2022
Matching Normalizing Flows and Probability Paths on Manifolds Heli Ben-Hamu Samuel N. Cohen Joey Bose Brandon Amos Aditya Grover Maximilian Nickel Ricky T. Q. Chen Y. Lipman 63 39 0 11 Jul 2022