In this review, we survey the latest approaches and techniques developed to overcome the spectral bias towards low frequency of deep neural network learning methods in learning multiple-frequency solutions of partial differential equations. Open problems and future research directions are also discussed.
@article{arxiv.2501.09987,
title = {On understanding and overcoming spectral biases of deep neural network learning methods for solving PDEs},
author = {Zhi-Qin John Xu and Lulu Zhang and Wei Cai},
journal= {arXiv preprint arXiv:2501.09987},
year = {2025}
}