Wasserstein loss: Revision history

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21 March 2023

  • curprev 22:2522:25, 21 March 2023‎ Walle talk contribs‎ 3,694 bytes +3,694‎ Created page with "{{see also|Machine learning terms}} ==Wasserstein Loss in Machine Learning== Wasserstein loss, also known as the Earth Mover's Distance (EMD), is a metric used in the field of machine learning, particularly in the training of Generative Adversarial Networks (GANs). Introduced by Martin Arjovsky, Soumith Chintala, and Léon Bottou in their 2017 paper "Wasserstein GAN," this loss function has become a popular choice for training GANs due to its stability and th..."
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