Reviews: Learned D-AMP: Principled Neural Network based Compressive Image Recovery

Summary of the work: The authors present a theoretically motivated NN architecture for solving inverse problems arising in compressed sensing. The network architecture arises from'unrolling' the denoiser-based approximate message passing (D-AMP) algorithm with convolutional denoiser networks inside. The work is nicely presented, and to my knowledge, original. The authors present competitive results on known benchmark data. Overall evaluation: I enjoyed reading this paper, well presented, theoretically motivated work. I was pleased to see that the method achieves very competitive performance in the end both in terms of accuracy and in terms of speed.