poloclub / robust-principles
Robust Principles: Architectural Design Principles for Adversarially Robust CNNs
☆21Updated last year
Alternatives and similar repositories for robust-principles:
Users that are interested in robust-principles are comparing it to the libraries listed below
- Official Code for Efficient and Effective Augmentation Strategy for Adversarial Training (NeurIPS-2022)☆16Updated last year
- Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]☆52Updated last year
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆18Updated 2 years ago
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆35Updated 3 years ago
- Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)☆25Updated 2 years ago
- Certified Patch Robustness via Smoothed Vision Transformers☆42Updated 3 years ago
- ☆22Updated 2 years ago
- A simple and efficient baseline for data attribution☆11Updated last year
- Code for a research paper "Part-Based Models Improve Adversarial Robustness" (ICLR 2023)☆22Updated last year
- Official Implementation for PlugIn Inversion☆15Updated 3 years ago
- Implementation of Confidence-Calibrated Adversarial Training (CCAT).☆45Updated 4 years ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated last year
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off☆29Updated 2 years ago
- Data-free knowledge distillation using Gaussian noise (NeurIPS paper)☆15Updated last year
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 2 years ago
- Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation☆44Updated last year
- SEAT☆20Updated last year
- Certified robustness "for free" using off-the-shelf diffusion models and classifiers☆36Updated last year
- OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift. ICML 2024 and ICLRW-DMLR 2024☆19Updated 5 months ago
- Official repository for "On Improving Adversarial Transferability of Vision Transformers" (ICLR 2022--Spotlight)☆70Updated 2 years ago
- [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”☆48Updated 3 years ago
- [NeurIPS2020] The official repository of "AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows".☆45Updated last year
- PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM☆23Updated 4 years ago
- Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective☆20Updated 7 months ago
- This repository provides code for "On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness".☆45Updated 2 years ago
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆46Updated 3 years ago
- [CVPR 2024] This repository includes the official implementation our paper "Revisiting Adversarial Training at Scale"☆18Updated 8 months ago
- This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.☆20Updated 2 years ago
- PDM-based Purifier☆18Updated 2 months ago
- Official implementation of "When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture" published at Neur…☆28Updated 4 months ago