Why is the variational auto-encoder's output blurred, while GANs output is crisp and has sharp edges?
What are the possible social consequences of training neural networks with artificially generated data?
Query regarding the minmax loss function formulation of the training of a Generative Adversarial Network (GAN)
What parameters can be tweaked to avoid a generator or discriminator loss collapsing to zero when training a DC-GAN?
How important is it that the generator of a generative adversarial network doesn't take in information about input classes?
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