I am reading about GANs. I understand that GANs learn implicitly the probability distribution that generated the data. However, at the input we give a random noise vector. It seems that we can sample that random noise vector from whatever distribution we want. My question is: given that there is ONLY ONE possible distribution that […]

## GANs and random noise

- Post author By Jessica Alba
- Post date June 30, 2020
- No Comments on GANs and random noise

- Tags and that our GAN is trying to approximate that distribution, as the random noise vector can be sampled from whatever distribution we want, at the input we give a random noise vector. It seems that we can sample that random noise vector from whatever distribution we want. My ques, but the GAN needs to be able to still imitate one unique distribution, can i think that the GAN also learns how to map between that distribution that it needs to learn and the distribution from which we sample th, I am reading about GANs. I understand that GANs learn implicitly the probability distribution that generated the data. However, so in a way it needs to be able to adapt to the distribution from which the noise comes., so it can be different each time we start to train, so it can vary