A projection step that forces a deep network's reconstruction to satisfy y = Ax gives small PSNR gains in low-noise imaging tests, but the supporting theory is a restatement of the definition of a well-trained network.
Specifically, the following proposition shows that a well-trained network exhibits a bias influenced by the covariance of the noise
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Projection-Based Correction for Enhancing Deep Inverse Networks
A projection step that forces a deep network's reconstruction to satisfy y = Ax gives small PSNR gains in low-noise imaging tests, but the supporting theory is a restatement of the definition of a well-trained network.