476 citations · 482 across the 2 of their papers we have counts for
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AMP-Inspired Deep Networks for Sparse Linear Inverse Problems
Mark Borgerding, Philip Schniter, Sundeep Rangan
Deep learning has gained great popularity due to its widespread success on many inference problems. We consider the application of deep learning to the sparse linear inverse proble…
Onsager-corrected deep learning for sparse linear inverse problems
Mark Borgerding, Philip Schniter
Deep learning has gained great popularity due to its widespread success on many inference problems. We consider the application of deep learning to the sparse linear inverse proble…
Generalized Approximate Message Passing for Cosparse Analysis Compressive Sensing
Mark Borgerding, Philip Schniter, Sundeep Rangan
In cosparse analysis compressive sensing (CS), one seeks to estimate a non-sparse signal vector from noisy sub-Nyquist linear measurements by exploiting the knowledge that a given…