Wednesday, 08 December 2021, 13:00 at Virtual (see abstract for Zoom link) – Deep networks provide state-of-the-art performance in multiple imaging inverse problems ranging from medical imaging to computational photography. In various imaging problems, we usually only have access to compressed measurements of the underlying signals, hindering most learning-based strategies which usually require pairs of signals and associated measurements for training. Learning only …