Title: On reproduction of On the regularization of Wasserstein GANs,
Abstract: This report has several purposes. First, our report is written to investigate
the reproducibility of the submitted paper On the regularization of Wasserstein
GANs (2018). Second, among the experiments performed in the submitted paper,
five aspects were emphasized and reproduced: learning speed, stability,
robustness against hyperparameter, estimating the Wasserstein distance, and
various sampling method. Finally, we identify which parts of the contribution
can be reproduced, and at what cost in terms of resources. All source code for
reproduction is open to the public.