5 citations · 5 across the 6 of their papers we have counts for
6 papers
Geometry-Aware Diffusion Guidance via Curvature-Adaptive Tubular Correction
Enze Jiang, Jinwei He, Zheng Ma
Gradient-guided diffusion samplers provide flexible priors for inverse problems and conditional generation, but strong guidance can move the sampling trajectory into regions where…
Analytic Distribution of Classifier-Free Guidance for Schedule Design
Enze Jiang, Zheng Ma
Classifier-free guidance (CFG) is the default mechanism for conditional generation in diffusion models, but the distribution sampled by its deterministic guided dynamics is not cap…
SSI-DM: Singularity Skipping Inversion of Diffusion Models
Chen Min, Enze Jiang, Jishen Peng +1
Inverting real images into the noise space is essential for editing tasks using diffusion models, yet existing methods produce non-Gaussian noise with poor editability due to the i…
Robust Physics-Guided Diffusion for Full-Waveform Inversion
Jishen Peng, Enze Jiang, Zheng Ma +1
We develop a robust physics-guided diffusion framework for full-waveform inversion that combines a score-based generative prior with likelihood guidance computed through wave-equat…
Quanta Video Restoration
Prateek Chennuri, Yiheng Chi, Enze Jiang +5
The proliferation of single-photon image sensors has opened the door to a plethora of high-speed and low-light imaging applications. However, data collected by these sensors are of…
ODE-DPS: ODE-based Diffusion Posterior Sampling for Inverse Problems in Partial Differential Equation
Enze Jiang, Jishen Peng, Zheng Ma +1
In recent years we have witnessed a growth in mathematics for deep learning, which has been used to solve inverse problems of partial differential equations (PDEs). However, most d…