Chapter 09.02: GAN variants

This subsection introduces key GAN variants that address limitations in traditional GAN training. It covers non-saturating loss, which helps avoid vanishing gradients. Conditional GANs are also discussed, where additional data, such as labels or images, is used to guide the generation process, enabling more controlled and targeted outputs.

Lecture slides