Resolution-Independent Analysis of Encoder--Decoder Operator Learning via Limiting Kernels

Operator learning is formulated on function spaces, but training data are typically available only through finite-dimensional representations. In encoder--decoder architectures, a matrix-valued kernel on the encoded space induces an operator-valued kernel on the original function spaces, and the cor