[david-gpu]

> So if you come up with some better way of telling apart real from fake, it can immediately be used as part of the discriminator

The generator can only learn from the discriminator if the discriminator is differentiable and has reasonably consistent gradients.

[bitL]

You can use relaxation for discrete variables (e.g. by using convex simplex), replacing them with differentiable variables, and then just discretize after the very end of the computation. A common trick for variational autoencoders that are another way to do generative models.

[currymj]

I sort of naively assumed that any binary classification task on images nowadays would be done with a deep NN.

Are there any proposed techniques for detecting fakes that can't be easily differentiated through?