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Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
Continuous Conditional Generative Adversarial Networks (CcGAN)
Computing the Sliding Fréchet Inception Distance between fake and real images with continous labels
some models with easy understand code
Efficient Subsampling of Realistic Images From GANs Conditional on a Class or a Continuous Variable