activity
20232026
collaborators

7 papers

cs.CV2026

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…

cs.CV2026

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…

cs.LG2026

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…

cs.LG2026

Decoupled Latent Optimization of Diffusion Models for Full Waveform Inversion

Chen Min, Zheng Ma

Full waveform inversion (FWI) recovers subsurface velocity from seismic recordings by solving a severely ill-posed, nonconvex PDE-constrained optimization. Classical regularizers s…

math.NA2026

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…

math.NA2024

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…

math.NA2023

An Unsupervised Deep Learning Approach for the Wave Equation Inverse Problem

Xiong-Bin Yan, Keke Wu, Zhi-Qin John Xu +1

Full-waveform inversion (FWI) is a powerful geophysical imaging technique that infers high-resolution subsurface physical parameters by solving a non-convex optimization problem. H…