Generative Adversarial Networks via a Composite Annealing of Noise and Diffusion
Generative Adversarial Networks via a Composite Annealing of Noise and Diffusion
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Generative adversarial network (GAN) is a framework for generating fake data using a set of real examples. However, GAN is unstable in the training stage. In order to stabilize GANs, the noise injection has been used to enlarge the overlap of the real and fake distributions at the cost of increasing variance. The diffusion (or smoothing) may reduce...
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Generative Adversarial Networks via a Composite Annealing of Noise and Diffusion
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TN_cdi_proquest_journals_2522250615
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2522250615
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2331-8422
