Wasserstein GAN
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| Authors | Soumith Chintala, Martin Arjovsky, Léon Bottou |
| Journal/Conference Name | IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops |
| Paper Category | Artificial Intelligence |
| Paper Abstract | We introduce a new algorithm named WGAN, an alternative to traditional GAN training. In this new model, we show that we can improve the stability of learning, get rid of problems like mode collapse, and provide meaningful learning curves useful for debugging and hyperparameter searches. Furthermore, we show that the corresponding optimization problem is sound, and provide extensive theoretical work highlighting the deep connections to other distances between distributions. |
| Date of publication | 2017 |
| Code Programming Language | Multiple |
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