CFG-GAN: Composite functional gradient learning of generative adversarial models
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Updated
Jul 9, 2020 - C++
Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network. GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset.
CFG-GAN: Composite functional gradient learning of generative adversarial models
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Released June 10, 2014