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Intermediate
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Generative Adversarial Networks (GANs)
GANs pit a generator against a discriminator to produce realistic data.
How does a GAN work?
A
A generator creates samples while a discriminator tries to tell real from fake, and they train against each other
B
A single network memorizes all training images
C
Two identical models vote on the correct answer
D
It uses no neural networks at all