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Lipschitz-regularized gradient flows and generative particle algorithms
  for high-dimensional scarce data

Lipschitz-regularized gradient flows and generative particle algorithms for high-dimensional scarce data

31 October 2022
Hyemin Gu
P. Birmpa
Yannis Pantazis
Luc Rey-Bellet
M. Katsoulakis
ArXivPDFHTML

Papers citing "Lipschitz-regularized gradient flows and generative particle algorithms for high-dimensional scarce data"

3 / 3 papers shown
Title
Combining Wasserstein-1 and Wasserstein-2 proximals: robust manifold
  learning via well-posed generative flows
Combining Wasserstein-1 and Wasserstein-2 proximals: robust manifold learning via well-posed generative flows
Hyemin Gu
M. Katsoulakis
Luc Rey-Bellet
Benjamin J. Zhang
24
2
0
16 Jul 2024
Wasserstein proximal operators describe score-based generative models
  and resolve memorization
Wasserstein proximal operators describe score-based generative models and resolve memorization
Benjamin J. Zhang
Siting Liu
Wuchen Li
M. Katsoulakis
Stanley J. Osher
DiffM
24
8
0
09 Feb 2024
A Good Score Does not Lead to A Good Generative Model
A Good Score Does not Lead to A Good Generative Model
Sixu Li
Shi Chen
Qin Li
DiffM
53
15
0
10 Jan 2024
1