Hello,
I’ve been wanting to get to know better GANs and I was wondering what could be a good entry point exercise. What do you think of a setting where the adversarial network would learn to generate sinus ?
You’d have various types of sinus, with different frequencies, different offsets described with, say, 256 points (neurons) and the adversarial network should learn the distribution of sinus. Does it sound logical, coherent, relevant ?
Thanks !