Generative Adversarial Network (GAN)
Two neural networks competing against each other to generate realistic synthetic data.
In-depth explanation
GANs consist of a generator (creates fake data) and discriminator (distinguishes real from fake). They're trained adversarially-the generator tries to fool the discriminator, while the discriminator tries not to be fooled. This competition drives both to improve. GANs excel at image synthesis, style transfer, and data augmentation.
Examples
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Hallucination
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