M4xim4l / InNOutRobustnessLinks
Adversarial Robustness on In- and Out-Distribution Improves Explainability
☆12Updated 3 years ago
Alternatives and similar repositories for InNOutRobustness
Users that are interested in InNOutRobustness are comparing it to the libraries listed below
Sorting:
- Understanding and Improving Fast Adversarial Training [NeurIPS 2020]☆95Updated 3 years ago
- ☆35Updated 4 years ago
- ☆13Updated 5 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 3 years ago
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated 2 years ago
- Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".☆55Updated 3 years ago
- Coupling rejection strategy against adversarial attacks (CVPR 2022)☆29Updated 3 years ago
- A Closer Look at Accuracy vs. Robustness☆89Updated 4 years ago
- Understanding Catastrophic Overfitting in Single-step Adversarial Training [AAAI 2021]☆27Updated 3 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 6 years ago
- Implementation of Confidence-Calibrated Adversarial Training (CCAT).☆45Updated 4 years ago
- Smooth Adversarial Training☆67Updated 4 years ago
- Code for the paper: Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization (https://arxiv.org/abs/2…☆23Updated 4 years ago
- Further improve robustness of mixup-trained models in inference (ICLR 2020)☆60Updated 5 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Official repository for "A Self-supervised Approach for Adversarial Robustness" (CVPR 2020--Oral)☆100Updated 4 years ago
- Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses, NeurIPS Spotlight 2020☆27Updated 4 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆32Updated 5 years ago
- [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.☆26Updated 11 months 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
- Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing the…☆55Updated 2 years ago
- A repository for the query-efficient black-box attack, SignHunter☆23Updated 5 years ago
- Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in ICCV 2019☆58Updated 5 years ago
- Feature Scattering Adversarial Training (NeurIPS19)☆73Updated last year
- ☆48Updated 4 years ago
- Code for "Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors"☆64Updated 5 years ago
- ☆40Updated last year
- Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"☆34Updated 5 years ago
- Learnable Boundary Guided Adversarial Training (ICCV2021)☆38Updated 7 months ago
- Codes for reproducing the experimental results in "Proper Network Interpretability Helps Adversarial Robustness in Classification", publi…☆13Updated 5 years ago