Methods › General › Neural Architecture Search › AutoGAN
AutoGAN
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Neural architecture search (NAS) has witnessed prevailing success in image classification and (very recently) segmentation tasks. In this paper, we present the first preliminary study on introducing the NAS algorithm to generative adversarial networks (GANs), dubbed AutoGAN. The marriage of NAS and GANs faces its unique challenges. We define the search space for the generator architectural variations and use an RNN controller to guide the search, with parameter sharing and dynamic-resetting to accelerate the process. Inception score is adopted as the reward, and a multi-level search strategy is introduced to perform NAS in a progressive way.
Papers archive 2025-07-28
2 shown of 2, 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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Adaptive Weighted Discriminator for Training Generative Adversarial Networks 5 Dec 2020 · 3 repositories · arXiv:2012.03149
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AutoGAN: Neural Architecture Search for Generative Adversarial Networks 11 Aug 2019 · 2 repositories · arXiv:1908.03835Syntology ran 1 of 5 samples · 4 unverified
Tasks archive 2025-07-28
7 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 |
|---|---|
| Image Generation | 2 |
| Unconditional Image Generation | 2 |
| Conditional Image Generation | 1 |
| Generative Adversarial Network | 1 |
| Image Classification | 1 |
| Neural Architecture Search | 1 |
| image-classification | 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
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