MTandHJ / robocLinks
An Orthogonal Classifier for Improving the Adversarial Robustness of Neural Networks
☆14Updated 3 years ago
Alternatives and similar repositories for roboc
Users that are interested in roboc are comparing it to the libraries listed below
Sorting:
- Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses, NeurIPS Spotlight 2020☆27Updated 4 years ago
- Code for Boosting fast adversarial training with learnable adversarial initialization (TIP2022)☆29Updated last year
- The official pytorch implementation of ACM MM 19 paper "MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks"☆11Updated 4 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 6 years ago
- Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks☆39Updated 4 years ago
- PyTorch adversarial attack baselines for ImageNet, CIFAR10, and MNIST (state-of-the-art attacks comparison)☆19Updated 4 years ago
- CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection☆20Updated 3 years ago
- Pytorch code for ens_adv_train☆15Updated 6 years ago
- Official Code for Efficient and Effective Augmentation Strategy for Adversarial Training (NeurIPS-2022)☆16Updated 2 years ago
- Understanding Catastrophic Overfitting in Single-step Adversarial Training [AAAI 2021]☆27Updated 3 years ago
- A PyTorch implementation of the method found in "Adversarially Robust Few-Shot Learning: A Meta-Learning Approach"☆49Updated 4 years ago
- ☆35Updated 4 years ago
- Learnable Boundary Guided Adversarial Training (ICCV2021)☆38Updated 6 months ago
- [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…☆44Updated 3 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 3 years ago
- Code for our NeurIPS 2020 paper Backpropagating Linearly Improves Transferability of Adversarial Examples.☆42Updated 2 years ago
- Adversarial Distributional Training (NeurIPS 2020)☆63Updated 4 years ago
- PyTorch implementation of "Feature Denoising for Improving Adversarial Robustness" on CIFAR10.☆36Updated 5 years ago
- [NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"☆45Updated 3 years ago
- Codes for reproducing the results of the paper "Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness" published at IC…☆27Updated 5 years ago
- Implementation of adversarial training under fast-gradient sign method (FGSM), projected gradient descent (PGD) and CW using Wide-ResNet-…☆40Updated 5 years ago
- [NeurIPS2021] Code Release of Learning Transferable Perturbations☆28Updated 6 months ago
- SEAT☆20Updated last year
- Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective☆20Updated last year
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated 2 years ago
- PyTorch implementations of Adversarial defenses and utils.☆34Updated last year
- Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"☆34Updated 5 years ago
- Code corresponding to the paper: "On the Robustness of Vision Transformers": https://arxiv.org/abs/2104.02610☆24Updated last year
- Code for the paper "Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks"☆12Updated 2 years ago
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off☆33Updated 3 years ago