In the context of Generative Adversarial Networks (GANs), a discriminator is a neural network that differentiates between real data and data generated by the generator. Its primary role is to assess the authenticity of the data it receives, providing feedback to the generator to improve its output. The discriminator is crucial for the adversarial training process, as it challenges the generator to produce increasingly realistic data.
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