Before revision:  We discuss the use of Wasserstein Generative Adversarial Networks ( WGANs) as a method for systematically generating artificial data that mimic closely any given real data set without the researcher having many degrees of freedom .
After revision:  We discuss the use of Wasserstein Generative Adversarial Networks ( GANs) that can be used to systematically generate artificial data that mimic closely any given real data set without the researcher having many degrees of freedom .