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eess.IV2024
Constructing an Interpretable Deep Denoiser by Unrolling Graph Laplacian Regularizer
Seyed Alireza Hosseini, Tam Thuc Do, Gene Cheung +1
An image denoiser can be used for a wide range of restoration problems via the Plug-and-Play (PnP) architecture. In this paper, we propose a general framework to build an interpret…
cs.LG2024★ 2 cited
Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors
Tam Thuc Do, Parham Eftekhar, Seyed Alireza Hosseini +2
We build interpretable and lightweight transformer-like neural networks by unrolling iterative optimization algorithms that minimize graph smoothness priors -- the quadratic graph…