Wasserstein Generative Adversarial Networks

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... (read more)

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METHOD TYPE
WGAN
Generative Adversarial Networks
Convolution
Convolutions
GAN
Generative Models