Jeongsu Lee

Legendre polynomial anti-derivative layer for compact physics-informed neural networks and operator learning with high-frequency spectral expressivity

Physics-informed neural networks (PINNs) with compact architectures often struggle to represent oscillatory and multiscale solutions when the representations formed by their hidden layers are insufficiently expressive. Here, we introduce a Legendre polynomial anti-derivative (LPA) layer as a structured readout activati...