Neural network based methods have emerged as a promising paradigm for scientific computing, yet they face critical bottlenecks in high frequency function approximation and partial differential equation (PDE) solving.
@article{arxiv.2604.03186,
title = {High-Precision Phase-Shift Transferable Neural Networks for High-Frequency Function Approximation and PDE Solution},
author = {Xuyang Gao and Liang Chen and Minqiang Xu and Jing Niu},
journal= {arXiv preprint arXiv:2604.03186},
year = {2026}
}