Unverified50% confidenceFactExact time
The core structure of a GAN contains two neural networks: the generator is responsible for generating realistic samples from random noise, and the discriminator is responsible for distinguishing whether an input sample is real or generated, with the two competing against each other during training and ideally reaching a Nash equilibrium.
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10/15/2026
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