Let's say we have a WGAN where the generator and critic have 8 layers and 5 million parameters each. I know that the greater the number of training samples the better, but is there a way to know the minimum number of training examples needed? Does it depend on the size of the network or the distribution of the training set? How can I estimate it?
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