To build the gap attack I first had to learn how to train a neural network, so this post is mostly the ML setup (CNNs, tensors, loss, gradient descent), with the working attack at the end.

The first in a series cataloguing my journey reproducing papers I want to properly understand. Starting with the core idea and vocabulary of membership inference attacks.