I am working on a class project where I compare the performance of GAN and WGAN. Since the only difference between GAN and WGAN is the Wasserstein loss, I chose one neural network model architecture and trained both GAN and WGAN (so, only the loss functions differ).
However, WGAN performs much worse than GAN, and I'm not sure why. Is the performance of Wasserstein loss model dependent? If had to compare GAN and WGAN, holding the NN architecture fixed, what architecture should I choose?