Methods › General › Regularization › Euclidean Norm Regularization
Euclidean Norm Regularization
Introduced by Yan Wu et al. in Deep Compressed Sensing
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Euclidean Norm Regularization is a regularization step used in generative adversarial networks, and is typically added to both the generator and discriminator losses:
R_z = wᵣ ·||Δz||²₂
where the scalar weight wᵣ is a parameter.
Image: LOGAN
Papers archive 2025-07-28
9 shown of 9, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Auditing Algorithmic Fairness in Machine Learning for Health with Severity-Based LOGAN 16 Nov 2022 · 0 repositories · arXiv:2211.08742
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Edge-based fever screening system over private 5G 8 Feb 2022 · 0 repositories · arXiv:2202.03917
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Sinogram Denoise Based on Generative Adversarial Networks 9 Aug 2021 · 0 repositories · arXiv:2108.03903
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Direct Reconstruction of Linear Parametric Images from Dynamic PET Using Nonlocal Deep Image Prior 18 Jun 2021 · 0 repositories · arXiv:2106.10359
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Volumetric Quantitative Ablation Margins for Assessment of Ablation Completeness in Thermal Ablation of Liver Tumors 10 Mar 2021 · 1 repository
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LOGAN: Local Group Bias Detection by Clustering 6 Oct 2020 · 1 repository · arXiv:2010.02867
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Allpass Feedback Delay Networks 14 Jul 2020 · 0 repositories · arXiv:2007.07337
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LOGAN: Latent Optimisation for Generative Adversarial Networks 2 Dec 2019 · 1 repository · arXiv:1912.00953Syntology ran 2 of 8 samples · 6 unverified
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Deep Compressed Sensing 16 May 2019 · 1 repository · arXiv:1905.06723
Tasks archive 2025-07-28
13 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Bias Detection | 2 |
| Clustering | 2 |
| BIG-bench Machine Learning | 1 |
| Computational Efficiency | 1 |
| Conditional Image Generation | 1 |
| Decision Making | 1 |
| Denoising | 1 |
| Edge-computing | 1 |
| Fairness | 1 |
| Generative Adversarial Network | 1 |
| Image Generation | 1 |
| Meta-Learning | 1 |
| compressed sensing | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections