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Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative
  Models
v1v2v3 (latest)

Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models

15 June 2023
Gen Li
Yuting Wei
Yuxin Chen
Yuejie Chi
    DiffM
ArXiv (abs)PDFHTML

Papers citing "Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models"

41 / 41 papers shown
Title
Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models
Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models
Yang Zheng
Wen Li
Zhaoqiang Liu
84
0
0
27 May 2025
Learning Single Index Models with Diffusion Priors
Learning Single Index Models with Diffusion Priors
Anqi Tang
Youming Chen
Shuchen Xue
Zhaoqiang Liu
DiffM
94
0
0
27 May 2025
Convergence Of Consistency Model With Multistep Sampling Under General Data Assumptions
Convergence Of Consistency Model With Multistep Sampling Under General Data Assumptions
Yiding Chen
Yiyi Zhang
Owen Oertell
Wen Sun
DiffM
95
1
0
06 May 2025
Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
Gen Li
Changxiao Cai
Yuting Wei
DiffM
82
1
0
07 Apr 2025
Fine-Tuning Diffusion Generative Models via Rich Preference Optimization
Fine-Tuning Diffusion Generative Models via Rich Preference Optimization
Hanyang Zhao
Haoxian Chen
Yucheng Guo
Genta Indra Winata
Tingting Ou
Ziyu Huang
D. Yao
Wenpin Tang
141
0
0
13 Mar 2025
Improved Diffusion-based Generative Model with Better Adversarial Robustness
Improved Diffusion-based Generative Model with Better Adversarial Robustness
Zekun Wang
Mingyang Yi
Shuchen Xue
Zhiyu Li
Ming Liu
Bing Qin
Zhi-Ming Ma
DiffM
116
0
0
24 Feb 2025
Regularization can make diffusion models more efficient
Regularization can make diffusion models more efficient
Mahsa Taheri
Johannes Lederer
173
0
0
13 Feb 2025
Information-Theoretic Proofs for Diffusion Sampling
Information-Theoretic Proofs for Diffusion Sampling
Galen Reeves
H. Pfister
DiffM
154
0
0
04 Feb 2025
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework
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
113
9
0
04 Oct 2024
Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis
Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis
Zikun Zhang
Zixiang Chen
Quanquan Gu
DiffM
163
5
0
03 Oct 2024
Posterior sampling via Langevin dynamics based on generative priors
Posterior sampling via Langevin dynamics based on generative priors
Vishal Purohit
Matthew Repasky
Jianfeng Lu
Qiang Qiu
Yao Xie
Xiuyuan Cheng
DiffM
80
2
0
02 Oct 2024
What does guidance do? A fine-grained analysis in a simple setting
What does guidance do? A fine-grained analysis in a simple setting
Muthu Chidambaram
Khashayar Gatmiry
Sitan Chen
Holden Lee
Jianfeng Lu
61
14
0
19 Sep 2024
Constrained Diffusion Models via Dual Training
Constrained Diffusion Models via Dual Training
Shervin Khalafi
Dongsheng Ding
Alejandro Ribeiro
113
4
0
27 Aug 2024
A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion
  Models
A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models
Gen Li
Yuting Wei
Yuejie Chi
Yuxin Chen
DiffM
134
27
0
05 Aug 2024
Convergence of the denoising diffusion probabilistic models for general noise schedules
Convergence of the denoising diffusion probabilistic models for general noise schedules
Yumiharu Nakano
DiffM
163
1
0
03 Jun 2024
Accelerating Diffusion Models with Parallel Sampling: Inference at
  Sub-Linear Time Complexity
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity
Haoxuan Chen
Yinuo Ren
Lexing Ying
Grant M. Rotskoff
102
23
0
24 May 2024
Model Free Prediction with Uncertainty Assessment
Model Free Prediction with Uncertainty Assessment
Yuling Jiao
Lican Kang
Jin Liu
Heng Peng
Heng Zuo
DiffM
85
0
0
21 May 2024
U-Nets as Belief Propagation: Efficient Classification, Denoising, and
  Diffusion in Generative Hierarchical Models
U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models
Song Mei
3DVAI4CEDiffM
101
13
0
29 Apr 2024
An Overview of Diffusion Models: Applications, Guided Generation,
  Statistical Rates and Optimization
An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization
Minshuo Chen
Song Mei
Jianqing Fan
Mengdi Wang
VLMMedImDiffM
124
59
0
11 Apr 2024
Provably Robust Score-Based Diffusion Posterior Sampling for
  Plug-and-Play Image Reconstruction
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction
Xingyu Xu
Yuejie Chi
DiffM
96
27
0
25 Mar 2024
Accelerating Convergence of Score-Based Diffusion Models, Provably
Accelerating Convergence of Score-Based Diffusion Models, Provably
Gen Li
Yu Huang
Timofey Efimov
Yuting Wei
Yuejie Chi
Yuxin Chen
DiffM
101
37
0
06 Mar 2024
Theoretical Insights for Diffusion Guidance: A Case Study for Gaussian
  Mixture Models
Theoretical Insights for Diffusion Guidance: A Case Study for Gaussian Mixture Models
Yuchen Wu
Minshuo Chen
Zihao Li
Mengdi Wang
Yuting Wei
110
29
0
03 Mar 2024
Critical windows: non-asymptotic theory for feature emergence in
  diffusion models
Critical windows: non-asymptotic theory for feature emergence in diffusion models
Marvin Li
Sitan Chen
DiffM
105
14
0
03 Mar 2024
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions:
  Alleviating Metastability by Denoising Diffusion
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion
Ye He
Kevin Rojas
Molei Tao
DiffM
122
11
0
27 Feb 2024
Convergence Analysis of Discrete Diffusion Model: Exact Implementation
  through Uniformization
Convergence Analysis of Discrete Diffusion Model: Exact Implementation through Uniformization
Hongrui Chen
Lexing Ying
120
16
0
12 Feb 2024
Towards a mathematical theory for consistency training in diffusion
  models
Towards a mathematical theory for consistency training in diffusion models
Gen Li
Zhihan Huang
Yuting Wei
117
18
0
12 Feb 2024
Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial
Score-based Diffusion Models via Stochastic Differential Equations -- a Technical Tutorial
Wenpin Tang
Hanyang Zhao
DiffM
122
27
0
12 Feb 2024
Convergence Analysis for General Probability Flow ODEs of Diffusion
  Models in Wasserstein Distances
Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances
Xuefeng Gao
Lingjiong Zhu
127
21
0
31 Jan 2024
Neural Network-Based Score Estimation in Diffusion Models: Optimization
  and Generalization
Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
Yinbin Han
Meisam Razaviyayn
Renyuan Xu
DiffM
140
16
0
28 Jan 2024
Contractive Diffusion Probabilistic Models
Contractive Diffusion Probabilistic Models
Wenpin Tang
Hanyang Zhao
DiffM
109
14
0
23 Jan 2024
A Good Score Does not Lead to A Good Generative Model
A Good Score Does not Lead to A Good Generative Model
Sixu Li
Shi Chen
Qin Li
DiffM
135
18
0
10 Jan 2024
A Note on the Convergence of Denoising Diffusion Probabilistic Models
A Note on the Convergence of Denoising Diffusion Probabilistic Models
S. Mbacke
Omar Rivasplata
DiffM
90
6
0
10 Dec 2023
Conditional Stochastic Interpolation for Generative Learning
Conditional Stochastic Interpolation for Generative Learning
Ding Huang
Jian Huang
Ting Li
Guohao Shen
BDLDiffM
87
4
0
09 Dec 2023
Convergence of flow-based generative models via proximal gradient
  descent in Wasserstein space
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space
Xiuyuan Cheng
Jianfeng Lu
Yixin Tan
Yao Xie
231
19
0
26 Oct 2023
Analysis of learning a flow-based generative model from limited sample
  complexity
Analysis of learning a flow-based generative model from limited sample complexity
Hugo Cui
Florent Krzakala
Eric Vanden-Eijnden
Lenka Zdeborová
DRL
86
20
0
05 Oct 2023
Deep Networks as Denoising Algorithms: Sample-Efficient Learning of
  Diffusion Models in High-Dimensional Graphical Models
Deep Networks as Denoising Algorithms: Sample-Efficient Learning of Diffusion Models in High-Dimensional Graphical Models
Song Mei
Yuchen Wu
DiffM
86
28
0
20 Sep 2023
Nearly $d$-Linear Convergence Bounds for Diffusion Models via Stochastic
  Localization
Nearly ddd-Linear Convergence Bounds for Diffusion Models via Stochastic Localization
Joe Benton
Valentin De Bortoli
Arnaud Doucet
George Deligiannidis
DiffM
113
117
0
07 Aug 2023
Learning Mixtures of Gaussians Using the DDPM Objective
Learning Mixtures of Gaussians Using the DDPM Objective
Kulin Shah
Sitan Chen
Adam R. Klivans
DiffM
100
42
0
03 Jul 2023
Error Bounds for Flow Matching Methods
Error Bounds for Flow Matching Methods
Joe Benton
George Deligiannidis
Arnaud Doucet
DiffM
111
38
0
26 May 2023
Improved Convergence of Score-Based Diffusion Models via
  Prediction-Correction
Improved Convergence of Score-Based Diffusion Models via Prediction-Correction
Francesco Pedrotti
J. Maas
Marco Mondelli
DiffM
115
15
0
23 May 2023
The probability flow ODE is provably fast
The probability flow ODE is provably fast
Sitan Chen
Sinho Chewi
Holden Lee
Yuanzhi Li
Jianfeng Lu
Adil Salim
DiffM
102
91
0
19 May 2023
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