poloclub / robust-principlesLinks
Robust Principles: Architectural Design Principles for Adversarially Robust CNNs 
☆23Updated last year
Alternatives and similar repositories for robust-principles
Users that are interested in robust-principles are comparing it to the libraries listed below
Sorting:
- Official Implementation for PlugIn Inversion☆16Updated 4 years ago
- Single Image Backdoor Inversion via Robust Smoothed Classifiers☆17Updated 2 years ago
- Certified Patch Robustness via Smoothed Vision Transformers☆42Updated 3 years ago
- Official Pytorch repo of CVPR'23 and NeurIPS'23 papers on understanding replication in diffusion models.☆113Updated last year
- Implementation of Confidence-Calibrated Adversarial Training (CCAT).☆45Updated 5 years ago
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆20Updated 2 years ago
- ICML 2024 Paper "Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies"☆16Updated last year
- [CVPR 2024] This repository includes the official implementation our paper "Revisiting Adversarial Training at Scale"☆20Updated last year
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆36Updated 4 years ago
- Official repository for "On Improving Adversarial Transferability of Vision Transformers" (ICLR 2022--Spotlight)☆72Updated 2 years ago
- Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]☆53Updated 2 years ago
- Official implementation of "When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture" published at Neur…☆34Updated last year
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off☆33Updated 3 years ago
- PDM-based Purifier☆22Updated 11 months ago
- Respect to the input tensor instead of paramters of NN☆21Updated 3 years ago
- ☆15Updated 3 years ago
- Code for AAAI 2024 paper: CR-SAM: Curvature Regularized Sharpness-Aware Minimization☆10Updated 11 months ago
- Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)☆25Updated 3 years ago
- Adversarial Augmentation Against Adversarial Attacks☆32Updated 2 years ago
- A Self-Consistent Robust Error (ICML 2022)☆69Updated 2 years ago
- Data-free knowledge distillation using Gaussian noise (NeurIPS paper)☆15Updated 2 years ago
- [ICML2023] Revisiting Data-Free Knowledge Distillation with Poisoned Teachers☆23Updated last year
- [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”☆48Updated 3 years ago
- Official repo of Progressive Data Expansion: data, code and evaluation☆29Updated last year
- Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion☆11Updated last year
- Code for "Don't trust your eyes: on the (un)reliability of feature visualizations" (ICML 2024)☆33Updated last year
- A Closer Look at Accuracy vs. Robustness☆88Updated 4 years ago
- [NeurIPS2020] The official repository of "AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows".☆48Updated 2 years ago
- ☆20Updated 2 years ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated 2 years ago