GANs: Generator and Discriminator
Min-max game theory, GAN training instability, mode collapse, DCGAN implementation.
What is a GAN?
A Generative Adversarial Network pits two networks against each other: a Generator that creates fake data and a Discriminator that judges real vs fake. They compete, and the generator learns to produce convincing samples.
The Adversarial Game
Think of a forger (generator) and a detective (discriminator). The forger improves fakes to fool the detective; the detective sharpens its eye. This arms race drives both to get better, until fakes look real.
All lessons in this course
- Autoencoders for Representation Learning
- Variational Autoencoders (VAE)
- GANs: Generator and Discriminator
- Conditional GANs and Style Transfer