3 papers
math.NA2025
Nearly Optimal Approximation Rates for Deep Super ReLU Networks on Sobolev Spaces
Yahong Yang, Yue Wu, Haizhao Yang +1
This paper introduces deep super ReLU networks (DSRNs) as a method for approximating functions in Sobolev spaces measured by Sobolev norms for with $m\ge…
cs.LG2025
Learn Singularly Perturbed Solutions via Homotopy Dynamics
Chuqi Chen, Yahong Yang, Yang Xiang +1
Solving partial differential equations (PDEs) using neural networks has become a central focus in scientific machine learning. Training neural networks for singularly perturbed pro…
cs.LG2025
Automatic Differentiation is Essential in Training Neural Networks for Solving Differential Equations
Chuqi Chen, Yahong Yang, Yang Xiang +1
Neural network-based approaches have recently shown significant promise in solving partial differential equations (PDEs) in science and engineering, especially in scenarios featuri…