D-VAE

Code for "Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders" at ICML 2024

We provide some scripts in some_scripts.sh, and some experimental results on CIFAR-10 dataset in google drive.

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
configs		configs
fast_autoaugment		fast_autoaugment
models		models
LICENSE		LICENSE
README.md		README.md
dataset.py		dataset.py
evaluator.py		evaluator.py
madrys.py		madrys.py
main.py		main.py
main_vae_disentangle.py		main_vae_disentangle.py
perturbation.py		perturbation.py
some_scripts.sh		some_scripts.sh
toolbox.py		toolbox.py
trainer.py		trainer.py
util.py		util.py

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