From GAN to WGAN
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- Jul 21, 2026
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[Updated on 2018-09-30: thanks to Yoonju, we have this post translated in Korean !] [Updated on 2019-04-18: this post is also available on arXiv .] Generative adversarial network (GAN) has shown great results in many generative tasks to replicate the real-world rich content such as images, human language, and music. It is inspired by game theory: two models, a generator and a critic, are competing with each other while making each other stronger at the same time. However, it is rather challengin
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A rigorous, well-illustrated walkthrough of why vanilla GANs are unstable and how Wasserstein distance fixes the gradient/convergence problems — useful grounding for anyone building or debugging generative models.
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