6 papers
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…
RT-APNN for Solving Gray Radiative Transfer Equations
Xizhe Xie, Wengu Chen, Zheng Ma +1
The Gray Radiative Transfer Equations (GRTEs) are high-dimensional, multiscale problems that pose significant computational challenges for traditional numerical methods. Current de…
Asymptotic-Preserving Neural Networks based on Even-odd Decomposition for Multiscale Gray Radiative Transfer Equations
Keke Wu, Xizhe Xie, Wengu Chen +2
We present a novel Asymptotic-Preserving Neural Network (APNN) approach utilizing even-odd decomposition to tackle the nonlinear gray radiative transfer equations (GRTEs). Our AP l…
Optimal Estimation of Shared Singular Subspaces across Multiple Noisy Matrices
Zhengchi Ma, Rong Ma
Estimating singular subspaces from noisy matrices is a fundamental problem with wide-ranging applications across various fields. Driven by the challenges of data integration and mu…
A Micro-Macro Decomposition-Based Asymptotic-Preserving Random Feature Method for Multiscale Radiative Transfer Equations
Jingrun Chen, Zheng Ma, Keke Wu
This paper introduces the Asymptotic-Preserving Random Feature Method (APRFM) for the efficient resolution of multiscale radiative transfer equations. The APRFM effectively address…
Capturing Shock Waves by Relaxation Neural Networks
Nan Zhou, Zheng Ma
In this paper, we put forward a neural network framework to solve the nonlinear hyperbolic systems. This framework, named relaxation neural networks(RelaxNN), is a simple and scala…