Methods › Computer Vision › Generative Adversarial Networks › LOGAN
LOGAN
Introduced by Yan Wu et al. in LOGAN: Latent Optimisation for Generative Adversarial Networks
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
LOGAN is a generative adversarial network that uses a latent optimization approach using natural gradient descent (NGD). For the Fisher matrix in NGD, the authors use the empirical Fisher F′ with Tikhonov damping:
F′ = g ·gᵀ + βI
They also use Euclidian Norm regularization for the optimization step.
For LOGAN's base architecture, BigGAN-deep is used with a few modifications: increasing the size of the latent source from $186$ to $256$, to compensate the randomness of the source lost when optimising z. 2, using the uniform distribution U(−1, 1) instead of the standard normal distribution N(0, 1) for p(z) to be consistent with the clipping operation, using leaky ReLU (with the slope of 0.2 for the negative part) instead of ReLU as the non-linearity for smoother gradient flow for (δf(z))/δz .
Papers archive 2025-07-28
6 shown of 6, 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.
-
Auditing Algorithmic Fairness in Machine Learning for Health with Severity-Based LOGAN 16 Nov 2022 · 0 repositories · arXiv:2211.08742
-
Sinogram Denoise Based on Generative Adversarial Networks 9 Aug 2021 · 0 repositories · arXiv:2108.03903
-
Direct Reconstruction of Linear Parametric Images from Dynamic PET Using Nonlocal Deep Image Prior 18 Jun 2021 · 0 repositories · arXiv:2106.10359
-
LOGAN: Local Group Bias Detection by Clustering 6 Oct 2020 · 1 repository · arXiv:2010.02867
-
Allpass Feedback Delay Networks 14 Jul 2020 · 0 repositories · arXiv:2007.07337
-
LOGAN: Latent Optimisation for Generative Adversarial Networks 2 Dec 2019 · 1 repository · arXiv:1912.00953Syntology ran 2 of 8 samples · 6 unverified
Tasks archive 2025-07-28
8 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 |
| Denoising | 1 |
| Fairness | 1 |
| Image Generation | 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