Meet Diffusion-GAN: A Novel GAN Framework That Leverages A Forward Diffusion Chain To Generate Gaussian-Mixture Distributed Instance Noise

Generative Adversarial Networks (or just GANs) have been widely used to generate synthetic data for different applications in recent years. The most commonly considered domain is computer vision, where GAN can be used, for instance, to generate photo-realistic high-resolution images. One of the main problems of GANs is the instability of their training process. A […]

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