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

26 October 2023

Yao Xie

Papers citing "Convergence of flow-based generative models via proximal gradient descent in Wasserstein space"

11 / 11 papers shown

Title
Convergence Analysis of the Wasserstein Proximal Algorithm beyond Geodesic Convexity Shuailong Zhu Xiaohui Chen 67 0 0 28 Jan 2025
Local Flow Matching Generative Models Chen Xu Xiuyuan Cheng Yao Xie 39 0 0 03 Jan 2025
Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis Zikun Zhang Zixiang Chen Quanquan Gu DiffM 47 3 0 03 Oct 2024
Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport Zhenyi Zhang Tiejun Li Peijie Zhou OT 141 5 0 01 Oct 2024
A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Models Gen Li Yuting Wei Yuejie Chi Yuxin Chen DiffM 30 21 0 05 Aug 2024
Stochastic Interpolants: A Unifying Framework for Flows and Diffusions M. S. Albergo Nicholas M. Boffi Eric Vanden-Eijnden DiffM 244 260 0 15 Mar 2023
Rectified Flow: A Marginal Preserving Approach to Optimal Transport Qiang Liu OT 116 83 0 29 Sep 2022
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
Image-to-Image Translation with Conditional Adversarial Networks Phillip Isola Jun-Yan Zhu Tinghui Zhou Alexei A. Efros SSeg 212 19,191 0 21 Nov 2016
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 166 596 0 22 Sep 2016