I am aware variations of GAN’s exist; i.e DCGAN, DiscoGAN, CicyleGAN; Source: https://github.com/eriklindernoren/PyTorch-GAN; My question is, what are the primary constructs that differentiate GANs?
I would imagine that having a specified network architecture acting as the Discriminator creates a variety of a GAN network, but I’m unsure and need clarification. Please let me know if this thinking is correct or not, and in addition please elaborate on what other factors lead to a variant GAN network.
Thank you very much!