Universal approximation has been proven for the proposed architecture and the analysis proves universality for a broad class of kernel-integral neural operators

We prove universal approximation for the resulting architecture; furthermore the approach we adopt in the analysis proves universality for a broad class of kernel-integral neural operators thereby uniting existing theory for a variety of operator learning methods.

http://arxiv.org/abs/2608.27256v1