Learned regularizers for inverse problems

DOI10.1007/978-3-030-98661-2_68zbMATH Open1547.9405MaRDI QIDQ6606473

Sebastian Lunz

Publication date: 16 September 2024

zbMATH Keywords

inverse problemsvariational regularizationdeep learning

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Cites Work

• Unnamed Item
• The Little Engine that Could: Regularization by Denoising (RED)
• A Bilevel Optimization Approach for Parameter Learning in Variational Models
• $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
• Solving ill-posed inverse problems using iterative deep neural networks
• Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
• Deep Convolutional Neural Network for Inverse Problems in Imaging
• NETT: solving inverse problems with deep neural networks
• Solving inverse problems using data-driven models

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