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

22 November 2023

Dong-Young Lim

Ömer Deniz Akyildiz

Sotirios Sabanis

Papers citing "On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates"

6 / 6 papers shown

Title
Wasserstein Convergence of Score-based Generative Models under Semiconvexity and Discontinuous Gradients Stefano Bruno Sotirios Sabanis DiffM 36 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 28 2 0 04 Jan 2025
Generating High Dimensional User-Specific Wireless Channels using Diffusion Models Taekyun Lee Juseong Park Hyeji Kim Jeffrey G. Andrews DiffM 19 3 0 05 Sep 2024
Diffusion Models are Minimax Optimal Distribution Estimators Kazusato Oko Shunta Akiyama Taiji Suzuki DiffM 61 84 0 03 Mar 2023
Convergence of score-based generative modeling for general data distributions Holden Lee Jianfeng Lu Yixin Tan DiffM 177 128 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 123 245 0 22 Sep 2022