A generative adversarial network works through a competitive dance between two neural networks: the generator and the discriminator. The Generator This network starts with random noise as input.

Generative adversarial networks, or GANs, are deep learning frameworks for unsupervised learning that utilize two neural networks. The two networks are pitted against each other, with one generating ...

The Data Science Lab. Generating Synthetic Data Using a Generative Adversarial Network (GAN) with PyTorch. Dr. James McCaffrey of Microsoft Research explains a generative adversarial network, a deep ...

More often than not, these systems build upon generative adversarial networks (GANs), which are two-part AI models consisting of a generator that creates samples and a discriminator that attempts ...

I can’t tell you for sure if we have reached peak GAN, but there are far more people messing around with them than there were a year ago, and that’s a great thing. Two undergraduates at ...