There are 4 repositories under adversarial-training topic.
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
PyTorch-1.0 implementation for the adversarial training on MNIST/CIFAR-10 and visualization on robustness classifier.
Pytorch-Named-Entity-Recognition-with-transformers
Code for the paper "Adversarial Self-supervised Contrastive Learning" (NeurIPS 2020)
Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"
Official code for Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection (CVPR 2022 oral)
Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples" & "Fixing Data Augmentation to Improve Adversarial Robustness" in PyTorch
Adversarial attacks on Deep Reinforcement Learning (RL)
Feature Scattering Adversarial Training (NeurIPS19)
Adversarial Distributional Training (NeurIPS 2020)
KitanaQA: Adversarial training and data augmentation for neural question-answering models
Migrate to PyTorch. Re-implementation of Bayesian Convolutional Neural Networks (BCNNs)
Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]
Consistency Regularization for Adversarial Robustness (AAAI 2022)
[WACV 2022] "Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity" by Xinyu Gong, Wuyang Chen, Tianlong Chen and Zhangyang Wang
Chainer implementation of Bayesian Convolutional Neural Networks (BCNNs)
[MICCAI 2023] Official code repository of paper titled "Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation" accepted in MICCAI 2023 conference.
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation (ICCV2021)
Code for the paper: Adversarial Training Against Location-Optimized Adversarial Patches. ECCV-W 2020.
Contains notebooks for the PAR tutorial at CVPR 2021.
Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"
Implementation of adversarial training under fast-gradient sign method (FGSM), projected gradient descent (PGD) and CW using Wide-ResNet-28-10 on cifar-10. Sample code is re-usable despite changing the model or dataset.
Learnable Boundary Guided Adversarial Training (ICCV2021)
Ensemble Adversarial Black-Box Attacks against Deep Learning Systems Trained by MNIST, USPS and GTSRB Datasets
Code for the paper "Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models"
Code for paper "Model-based Adversarial Meta-Reinforcement Learning" (https://arxiv.org/abs/2006.08875)
Keras with Tensorflow implementation of our paper "Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces" which is published in IEEE Transactions on Information Forensics and Security (TIFS).
[NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training