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