85 citations · 99 across the 2 of their papers we have counts for
2 papers
math.NA2024★ 14 cited
An extrapolation-driven network architecture for physics-informed deep learning
Yong Wang, Yanzhong Yao, Zhiming Gao
Current PINN implementations with sequential learning strategies often experience some weaknesses, such as the failure to reproduce the previous training results when using a singl…
cs.LG2023★ 85 cited
A practical PINN framework for multi-scale problems with multi-magnitude loss terms
Yong Wang, Yanzhong Yao, Jiawei Guo +1
For multi-scale problems, the conventional physics-informed neural networks (PINNs) face some challenges in obtaining available predictions. In this paper, based on PINNs, we propo…