Learned Regularization for Inverse Problems: Insights from a Spectral
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Learned Regularization for Inverse Problems: Insights from a Spectral Model

15 December 2023

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Papers citing "Learned Regularization for Inverse Problems: Insights from a Spectral Model"

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Title
Learned reconstruction methods with convergence guarantees Subhadip Mukherjee A. Hauptmann Ozan Oktem Marcelo Pereyra Carola-Bibiane Schönlieb 70 51 0 11 Jun 2022
Learning convex regularizers satisfying the variational source condition for inverse problems Subhadip Mukherjee Antonio Bonafonte Mateusz Lajszczak 43 9 0 24 Oct 2021
Adversarial Regularizers in Inverse Problems Sebastian Lunz Ozan Oktem Carola-Bibiane Schönlieb GAN MedIm 84 220 0 29 May 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 83 529 0 28 May 2018
Deep learning for undersampled MRI reconstruction Chang Min Hyun Hwa Pyung Kim S. Lee Sungchul Lee J.K. Seo 53 457 0 08 Sep 2017
Learned Primal-dual Reconstruction J. Adler Ozan Oktem MedIm 60 752 0 20 Jul 2017
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems Tim Meinhardt Michael Möller C. Hazirbas Daniel Cremers 63 356 0 11 Apr 2017
Deep Convolutional Neural Network for Inverse Problems in Imaging Kyong Hwan Jin Michael T. McCann Emmanuel Froustey M. Unser 71 2,119 0 11 Nov 2016