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Wasserstein Generative Adversarial Networks
Wasserstein Generative Adversarial Networks
Martín Arjovsky,Soumith Chintala,L. Bottou
2017 · DBLP: conf/icml/ArjovskyCB17
International Conference on Machine Learning · 8,863 citations
TLDR
This work introduces a new algorithm named WGAN, an alternative to traditional GAN training that can improve the stability of learning, get rid of problems like mode collapse, and provide meaningful learning curves useful for debugging and hyperparameter searches.
