Self-study on GANs
This repo holds notes, experiments, references -> "the works" for learning the basics of GANs and how to apply them.
Paradigm
The idea, besides "learning GANs" is to apply the study in a "the Feynman-method" kind of way. Thus, reading a bit, then explain it, and hopefully identify parts that are unclear to motivate for further reading - and so forth.
Disclaimer
This is a personal repo and everything should be at this point taken "with a gram of salt".
TODO
Checkout Justin Johnsons course on Deep Learning for Computer Vision (they have two lectures on generative models): https://web.eecs.umich.edu/~justincj/teaching/eecs498/WI2022/