Physics-Informed Neural Networks for High-Frequency and Multi-Scale Problems Using Transfer Learning
Physics-Informed Neural Networks for High-Frequency and Multi-Scale Problems Using Transfer Learning
Physics-Informed Neural Network (PINN) is a data-driven solver for partial and ordinary differential equations (ODEs/PDEs). It provides a unified framework to address both forward and inverse problems. However, the complexity of the objective function often leads to training failures. This issue is particularly prominent when solving high-frequency and multi-scale problems. …