AdversarialNetsPapers
This collection gathers a wide range of papers and code concerning Generative Adversarial Networks (GANs), offering insights into applications such as image translation and facial attribute manipulation. It also delves into theoretical perspectives and machine learning methods with interdisciplinary applications in fields like medicine and music. Featuring advancements in autoML, image animation, and GAN theory, this repository serves researchers and developers interested in exploring GAN technology comprehensively. This resource ensures an extensive understanding of GANs' impact across varied domains.
