An Open-Source Package for Textual Adversarial Attack.
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Updated
Jul 20, 2023 - Python
An Open-Source Package for Textual Adversarial Attack.
A Harder ImageNet Test Set (CVPR 2021)
Pytorch implementation of convolutional neural network adversarial attack techniques
Simple pytorch implementation of FGSM and I-FGSM
A non-targeted adversarial attack method, which won the first place in NIPS 2017 non-targeted adversarial attacks competition
Tensorflow Implementation of Adversarial Attack to Capsule Networks
Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural training.
PyTorch library for adversarial attack and training
Generative Adversarial Perturbations (CVPR 2018)
Code for the CVPR 2019 article "Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses"
A targeted adversarial attack method, which won the NIPS 2017 targeted adversarial attacks competition
Spatially Transformed Adversarial Examples with TensorFlow
Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks
[ICML 2019] ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
Experiments with distributionally robust optimization (DRO) for deep neural networks
A simple implement of an Adversarial Autoencoding ATN(AAE ATN)
TensorFlow version of SqueezeNet with converted pretrained weights
code for ACL 2018 paper by Kang et al., "AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples "
This is a toolbox to construct adversarial examples of EEG signals. The traditional EEG extraction methods and classifiers are re-implemented in Tensorflow.
reproduction of Thermometer Encoding: One Hot Way To Resist Adversarial Examples in pytorch
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