Paper accepted at “Applied Soft Computing” Journal
Title: GNS-GAN: A novel GAN model based on gradient noise suppression Authors: Hongyou Chen, Lingfeng Qu, Baodan Tian, Yutong He, Yong Fan, Hadi Amirpour, Christian Timmerer and Yao Xin Journal: Applied Soft Computing Abstract: Generative adversarial networks (GANs) are widely applicable generative models. However, ensuring stability in adversarial learning remains a significant challenge in current GAN training. Gradient noise, […]
