Ze-Yuan Song

Theory Guided and Interpretable Neural Operator Design for Partial Differential Equation Learning

This work introduces a novel neural PDE solver named AFDONet, which incorporates neural operator learning and adaptive Fourier decomposition (AFD) theory for the first time into a specifically designed variational autoencoder (VAE) structure, to solve a general class of nonlinear PDEs on smooth manifolds.