Deep Learning, Artificial Intelligence, Gan, Generative Adversarial, Wgan.
the loss blew up and samples got worse. WGAN is summarized as below: (Lines 3–4): Each time, sample a batch of real samples, as well as a batch of fake samples from distribution z. (Lines 5): f is the critic model and g is the generator. The output layer of the critic model f is the linear