Generative Adversarial Network (GAN)

A GAN consists of two competing neural networks: a generator and a discriminator. The generator creates new data samples, like images or text, while the discriminator tries to distinguish between real data and the generator's fakes. Through this adversarial process, the generator learns to produce increasingly realistic outputs.