https://www.selleckchem.com/pr....oducts/coelenterazin
We propose a novel integral probability metric-based generative adversarial network (GAN), called SphereGAN. In the proposed scheme, the distance between two probability distributions (i.e., true and fake distributions) is measured on a hypersphere. Given that its hypersphere-based objective function computes the upper bound of the distance as a half arc, SphereGAN can be stably trained and can achieve a high convergence rate. In SphereGAN, higher-order information of data is processed using multiple geometric moments, thus impro
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