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Code for "Formulating Robustness Against Unforeseen Attacks"

The code for experiments performed in the paper are organized as follows:

  • train: this directory contains code for training models using $\ell_2$ and $\ell_\infty$ source threat models.
  • eval: this directory contains code for evaluating models trained using $\ell_2$ and $\ell_\infty$ source threat models.
  • perceptual_var: the code within this directory is used for training and evaluating models trained with non-$\ell_p$ sources corresponding to experiments in Appendix F.1.8.
  • Unseen_toy.ipynb: contains the code for experiments with linear models on Gaussian data located in Appendix E

Setting up:

pip install -r requirements.txt

For directions on running training and evaluation, please refer to the README located within each subdirectories.

Pretrained models:

  • For $\ell_2$ and $\ell_\infty$ sources (these should be evaluated with code in eval directory): models
  • For PAT-VR, StAdv, and ReColor sources (these should be evaluated with code in perceptual_var directory): models

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Official code for the paper "Formulating Robustness Against Unforeseen Attacks"

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