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There's just no point getting fancy for MNIST. Using nothing but fully-connected layers and rmsprop, I got good results in less than one minute. https://imgur.com/a/7xzmQ

Hidden units for discriminator layers - 100, 40, 2.

Generator layers - 40, 100, 768, then "reshape" into 28x28x1.

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Unlike regular classification, it's hard to quantify the performance of a GAN by just looking at the loss curves. You really have to make a subjective evaluation by looking at the generated images.

By playing around with it, the results I got from fully connected were nowhere near as good as the results I got from convolutional.

what you're showing is basically perfect discriminator with awful generator, isn't it?

Yeah ok it's pretty misleading. And if you let it run longer the generator starts getting a little better. It took me a long time to figure out the UI.

well you have the example on the left of graphs.

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