1 citations · 1 across the 4 of their papers we have counts for
4 papers
Provable Diffusion Posterior Sampling for Bayesian Inversion
Jinyuan Chang, Chenguang Duan, Yuling Jiao +3
We propose a novel diffusion-based posterior sampling method within a plug-and-play framework. Our approach constructs a probability transport from an easy-to-sample distribution t…
DRM Revisited: A Complete Error Analysis
Yuling Jiao, Ruoxuan Li, Peiying Wu +2
In this work, we address a foundational question in the theoretical analysis of the Deep Ritz Method (DRM) under the over-parameteriztion regime: Given a target precision level, ho…
Characteristic Learning for Provable One Step Generation
Zhao Ding, Chenguang Duan, Yuling Jiao +3
We propose the characteristic generator, an one-step generative model that combines the sampling efficiency of generative adversarial networks (GANs) with the training stability of…
Deep conditional distribution learning via conditional Föllmer flow
Jinyuan Chang, Zhao Ding, Yuling Jiao +2
We introduce an ordinary differential equation (ODE) based deep generative method for learning conditional distributions, named Conditional Föllmer Flow. Starting from a standard G…