Repository with code to reproduce the results for SMUG in our paper.
In this work, we propose SMUG that systematically integrates RS with MoDL using a deep unrolled architecture. We study in detail where to apply RS in the unrolled architecture for better performance and propose a novel unrolling loss to improve training efficiency. We show that the proposed SMUG is significantly effective in improving three major types of instabilities of MoDL.