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Generative Adversarial Networks (GANs)

concept · part of Generative AI Models

A generative AI model using a competitive framework of a generator and a discriminator to create realistic outputs. Suitable for realistic image creation.

GANs are particularly effective for tasks like image-to-image translation, super-resolution, and data augmentation. The generator learns to map random noise to the data distribution, while the discriminator distinguishes real from generated samples, leading to a minimax game that converges to a Nash equilibrium.

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