Reviews: Stabilizing Training of Generative Adversarial Networks through Regularization

This paper proposed to stabilize the training of GAN using proposed gradient-norm regularizer. This regularization is designed for conventional GAN, or more general f-GAN proposed last year. The idea is interesting but the justification is a little bit coarse. However, the regularizer defined in (21) is for arbitrary \psi, which contradicts this assumption. The authors claim that'the results clearly demonstrate the robustness of the regularizer w.r.t. the various regularization bandwidths'.