locuslab / robust_union
[ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.
☆25Updated last month
Related projects: ⓘ
- Source code for the paper "Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness"☆26Updated 4 years ago
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated last year
- Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"☆34Updated 4 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 2 years ago
- Implementation of Confidence-Calibrated Adversarial Training (CCAT).☆45Updated 4 years ago
- Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".☆54Updated 2 years ago
- Understanding and Improving Fast Adversarial Training [NeurIPS 2020]☆94Updated 2 years ago
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆15Updated last year
- Codebase for "Exploring the Landscape of Spatial Robustness" (ICML'19, https://arxiv.org/abs/1712.02779).☆26Updated 5 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆31Updated 4 years ago
- Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength☆37Updated 4 years ago
- Code for Stability Training with Noise (STN)☆21Updated 3 years ago
- Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).☆22Updated 2 years ago
- ☆85Updated last month
- Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs☆96Updated 3 years ago
- A Closer Look at Accuracy vs. Robustness☆87Updated 3 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆57Updated 5 years ago
- Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)☆25Updated last year
- Code for "Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors"☆61Updated 4 years ago
- [NeurIPS 2021] Fast Certified Robust Training with Short Warmup☆23Updated last year
- Code for the paper "Understanding Generalization through Visualizations"☆60Updated 3 years ago
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆45Updated 2 years ago
- RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)☆54Updated 3 years ago
- MACER: MAximizing CErtified Radius (ICLR 2020)☆27Updated 4 years ago
- Feature Scattering Adversarial Training (NeurIPS19)☆71Updated 3 months ago
- Adversarially Robust Transfer Learning with LWF loss applied to the deep feature representation (penultimate) layer☆17Updated 4 years ago
- Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"☆23Updated 5 years ago
- Code for the paper "Adversarial Neural Pruning with Latent Vulnerability Suppression"☆14Updated last year
- Adversarial Defense for Ensemble Models (ICML 2019)☆60Updated 3 years ago
- Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks☆36Updated 3 years ago