10 giug 2014 anni - Concept of Generative Adversarial Networks introduced

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Ian Goodfellow and collaborators introduce Generative Adversarial Networks (GANs) in their paper presented at the NIPS conference. GANs consist of two neural networks—a generator and a discriminator—that are trained simultaneously in a competitive setting. The generator creates synthetic data samples, while the discriminator attempts to distinguish them from real data. This framework lays the groundwork for significant advancements in generative modeling, particularly in image synthesis, and becomes a foundational concept in AI research.

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