High-Precision Phase-Shift Transferable Neural Networks for High-Frequency Function Approximation and PDE Solution

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.