Methods › Computer Vision › Generative Adversarial Networks › WGAN GP
Wasserstein GAN (Gradient Penalty)
WGAN GP
Introduced by Ishaan Gulrajani et al. in Improved Training of Wasserstein GANs
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Wasserstein GAN + Gradient Penalty, or WGAN-GP, is a generative adversarial network that uses the Wasserstein loss formulation plus a gradient norm penalty to achieve Lipschitz continuity.
The original WGAN uses weight clipping to achieve 1-Lipschitz functions, but this can lead to undesirable behaviour by creating pathological value surfaces and capacity underuse, as well as gradient explosion/vanishing without careful tuning of the weight clipping parameter c.
A Gradient Penalty is a soft version of the Lipschitz constraint, which follows from the fact that functions are 1-Lipschitz iff the gradients are of norm at most 1 everywhere. The squared difference from norm 1 is used as the gradient penalty.
Papers archive 2025-07-28
11 shown of 11, 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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FairGAN: GANs-based Fairness-aware Learning for Recommendations with Implicit Feedback 25 Apr 2022 · 1 repository
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Alleviating Mode Collapse in GAN via Diversity Penalty Module 5 Aug 2021 · 0 repositories · arXiv:2108.02353
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PriorGAN: Real Data Prior for Generative Adversarial Nets 30 Jun 2020 · 1 repository · arXiv:2006.16990
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Mimicry: Towards the Reproducibility of GAN Research 5 May 2020 · 3 repositories · arXiv:2005.02494
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Generating Geological Facies Models with Fidelity to Diversity and Statistics of Training Images using Improved Generative Adversarial Networks 23 Sep 2019 · 0 repositories · arXiv:1909.10652
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How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach 10 Jan 2019 · 2 repositories · arXiv:1901.03419
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Convolutional Generative Adversarial Networks with Binary Neurons for Polyphonic Music Generation 25 Apr 2018 · 3 repositories · arXiv:1804.09399Syntology ran 0 of 35 samples · 35 unverified
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Language Modeling with Generative AdversarialNetworks 8 Apr 2018 · 0 repositories · arXiv:1804.02617
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GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium 26 Jun 2017 · 71 repositories · arXiv:1706.08500Syntology ran 3 of 4 samples · 1 unverified · 1 pointer-only (licence)
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Continual Learning with Deep Generative Replay 24 May 2017 · 5 repositories · arXiv:1705.08690
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Improved Training of Wasserstein GANs 31 Mar 2017 · 110 repositories · arXiv:1704.00028Syntology ran 27 of 49 samples · 22 unverified · 20 pointer-only (licence)
Tasks archive 2025-07-28
20 shown of 26 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 | 3 |
| Diversity | 2 |
| Generative Adversarial Network | 2 |
| Class Incremental Learning | 1 |
| Conditional Image Generation | 1 |
| Continual Learning | 1 |
| Data Augmentation | 1 |
| Decision Making | 1 |
| Disentanglement | 1 |
| Emotion Recognition in Conversation | 1 |
| Exposure Fairness | 1 |
| Fairness | 1 |
| General Classification | 1 |
| Hippocampus | 1 |
| Image Classification | 1 |
| Image Super-Resolution | 1 |
| Language Modeling | 1 |
| Language Modelling | 1 |
| Music Generation | 1 |
| Recommendation Systems | 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