This repository is growing and will contain all my explorations wrt adversarial perturbations, attacks and robustness. My interest in this field comes from mechanistic interpretability, any code/musings related to the saem with live here.

Contents

• adversarial_ml.ipynb is an explantory jupyter notebook covering robust/non-robust features, adversarial attacks and robust ML models.

Acknowledgements and resources

For adversarial attacks and robustness:

• https://adversarial-ml-tutorial.org/introduction by Zico and Aleksander
• https://proceedings.neurips.cc/paper_files/paper/2019/file/e2c420d928d4bf8ce0ff2ec19b371514-Paper.pdf (Adversarial Examples are not Bugs, they are Features)