An empirical study proposing DeMUN, a memory-based unrolled network, and finding that intermediate loss and residual connections improve reconstruction while projector depth beyond five layers matters little.
Donoho, Arian Maleki, and Andrea Montanari
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Comprehensive Examination of Unrolled Networks for Solving Linear Inverse Problems
An empirical study proposing DeMUN, a memory-based unrolled network, and finding that intermediate loss and residual connections improve reconstruction while projector depth beyond five layers matters little.