FEDONet : Fourier-Embedded DeepONet for Spectrally Accurate Operator Learning

ArXi:2509.12344v4 Announce Type: replace Deep Operator Networks (DeepONets) have recently emerged as powerful data-driven frameworks for learning nonlinear operators, particularly suited for approximating solutions to partial differential equations. Despite their promising capabilities, the standard implementation of DeepONets, which typically employs fully connected linear layers in the trunk network, can encounter limitations in capturing complex spatial structures inherent to various PDEs.