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Proximal Splitting Networks for Image Restoration
This is in contrast to the common practice in literature of having the prior to be fixed and fully instantiated even during training stages.
Douglas-Rachford Networks: Learning Both the Image Prior and Data Fidelity Terms for Blind Image Deconvolution
These image recovery problems typically have two terms, the data fidelity term (for faithful reconstruction) and the image prior (for realistic looking reconstructions).
On Robust Learning from Noisy Labels: A Permutation Layer Approach
We provide two variants of PermLL in this paper: one applies the permutation layer to the model's prediction, while the other applies it directly to the given noisy label.
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