Generative Adversarial, Computer Vision, Gan, Machine Learning, Computer Science.
efficient training. Additionally, WGANs can also be used in semi-supervised learning settings, where a limited amount of labeled data is available. Wasserstein Generative Adversarial Networks (WGANs) was first introduced in a paper by Martin Arjovsky, Soumith Chintala, and Léon Bottou in 2017,