Alexander Auras

A neural operator view on U-Nets for inverse imaging problems

This work reviews common approaches to neural operator learning in architectures that resemble a U-Net, one of the most common classical architectures for inverse imaging problems, and studies how well networks trained for a certain resolution of the discretization generalize to other resolutions.