4 papers
Classifier-Free Guidance in Flow Matching: Non-Autonomous Potentials, Overshoot, and Posterior-Mean Control
Jishen Peng, Zheng Ma
Classifier-free guidance (CFG) improves conditional generation in Flow Matching, but strong guidance can distort the generated distribution and reduce diversity. We provide a geome…
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…
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…