Generative adversarial network

Generative adversarial network
Generative adversarial network, two neural netwoks contesting against each other

A generative adversarial network (GAN) is a type of generative model in machine learning that uses two neural networks contesting against each other to generate new data. Key characteristics:

GAN architectures include:

Applications of GANs include creating photorealistic media, data augmentation, image-to-image translation, and domain transfer learning.

GAN training can be unstable and prone to issues like mode collapse. But overall, GANs represent a major advance in generative modeling and unsupervised learning.

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