Learning Mixtures of Gaussians Using the DDPM Objective

3 July 2023

Papers citing "Learning Mixtures of Gaussians Using the DDPM Objective"

8 / 8 papers shown

Title
On the Generalization Properties of Diffusion Models Puheng Li Zhong Li Huishuai Zhang Jiang Bian 64 29 0 13 Mar 2025
Understanding Classifier-Free Guidance: High-Dimensional Theory and Non-Linear Generalizations Krunoslav Lehman Pavasovic Jakob Verbeek Giulio Biroli Marc Mézard 59 0 0 11 Feb 2025
Nonequilbrium physics of generative diffusion models Zhendong Yu Haiping Huang DiffM AI4CE 26 4 0 20 May 2024
U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models Song Mei 3DV AI4CE DiffM 31 11 0 29 Apr 2024
On the Asymptotic Mean Square Error Optimality of Diffusion Models B. Fesl Benedikt Bock Florian Strasser Michael Baur M. Joham Wolfgang Utschick DiffM 26 0 0 05 Mar 2024
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
Improved Convergence Guarantees for Learning Gaussian Mixture Models by EM and Gradient EM Nimrod Segol B. Nadler 19 11 0 03 Jan 2021