Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

15 March 2023

Papers citing "Stochastic Interpolants: A Unifying Framework for Flows and Diffusions"

9 / 9 papers shown

Title
Flow Along the K-Amplitude for Generative Modeling Weitao Du Shuning Chang Jiasheng Tang Yu Rong F. Wang Shengchao Liu 39 63 0 27 Apr 2025
Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport Zhenyi Zhang Tiejun Li Peijie Zhou OT 112 87 0 01 Oct 2024
Aligned Diffusion Schrödinger Bridges Vignesh Ram Somnath Matteo Pariset Ya-Ping Hsieh María Rodríguez Martínez Andreas Krause Charlotte Bunne DiffM 83 14 0 22 Feb 2023
Rectified Flow: A Marginal Preserving Approach to Optimal Transport Qiang Liu OT 99 40 0 29 Sep 2022
Convergence of score-based generative modeling for general data distributions Holden Lee Jianfeng Lu Yixin Tan DiffM 165 92 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 110 161 0 22 Sep 2022
Matching Normalizing Flows and Probability Paths on Manifolds Heli Ben-Hamu Samuel N. Cohen Joey Bose Brandon Amos Aditya Grover Maximilian Nickel Ricky T. Q. Chen Y. Lipman 39 31 0 11 Jul 2022
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory T. Chen Guan-Horng Liu Evangelos A. Theodorou DiffM OT 140 117 0 21 Oct 2021
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 91 83 0 10 Dec 2020