ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2303.01861
  4. Cited By
Diffusion Models are Minimax Optimal Distribution Estimators

Diffusion Models are Minimax Optimal Distribution Estimators

3 March 2023
Kazusato Oko
Shunta Akiyama
Taiji Suzuki
    DiffM
ArXivPDFHTML

Papers citing "Diffusion Models are Minimax Optimal Distribution Estimators"

14 / 14 papers shown
Title
Wasserstein Convergence of Score-based Generative Models under Semiconvexity and Discontinuous Gradients
Wasserstein Convergence of Score-based Generative Models under Semiconvexity and Discontinuous Gradients
Stefano Bruno
Sotirios Sabanis
DiffM
41
0
0
06 May 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
Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models
Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models
Gen Li
Yuling Yan
DiffM
44
18
0
03 Jan 2025
Diffusing States and Matching Scores: A New Framework for Imitation Learning
Diffusing States and Matching Scores: A New Framework for Imitation Learning
Runzhe Wu
Yiding Chen
Gokul Swamy
Kianté Brantley
Wen Sun
DiffM
37
3
0
17 Oct 2024
On the Relation Between Linear Diffusion and Power Iteration
On the Relation Between Linear Diffusion and Power Iteration
Dana Weitzner
M. Delbracio
P. Milanfar
Raja Giryes
DiffM
29
0
0
16 Oct 2024
Linear Convergence of Diffusion Models Under the Manifold Hypothesis
Linear Convergence of Diffusion Models Under the Manifold Hypothesis
Peter Potaptchik
Iskander Azangulov
George Deligiannidis
DiffM
35
5
0
11 Oct 2024
Differentially Private Kernel Density Estimation
Differentially Private Kernel Density Estimation
Erzhi Liu
Jerry Yao-Chieh Hu
Alex Reneau
Zhao Song
Han Liu
61
3
0
03 Sep 2024
On the optimal approximation of Sobolev and Besov functions using deep
  ReLU neural networks
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networks
Yunfei Yang
48
2
0
02 Sep 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
33
22
0
05 Aug 2024
Model Free Prediction with Uncertainty Assessment
Model Free Prediction with Uncertainty Assessment
Yuling Jiao
Lican Kang
Jin Liu
Heng Peng
Heng Zuo
DiffM
28
0
0
21 May 2024
Ensemble Successor Representations for Task Generalization in
  Offline-to-Online Reinforcement Learning
Ensemble Successor Representations for Task Generalization in Offline-to-Online Reinforcement Learning
Changhong Wang
Xudong Yu
Chenjia Bai
Qiaosheng Zhang
Zhen Wang
38
1
0
12 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
3DV
AI4CE
DiffM
36
11
0
29 Apr 2024
On diffusion-based generative models and their error bounds: The
  log-concave case with full convergence estimates
On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates
Stefano Bruno
Ying Zhang
Dong-Young Lim
Ömer Deniz Akyildiz
Sotirios Sabanis
DiffM
27
4
0
22 Nov 2023
Closed-Form Diffusion Models
Closed-Form Diffusion Models
Christopher Scarvelis
Haitz Sáez de Ocáriz Borde
Justin Solomon
DiffM
95
9
0
19 Oct 2023
1