neurips19-certificates-of-robustness
Robustness certificates
Tight certificates of adversarial robustness for randomly smoothed classifiers
"Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers" (NeurIPS 2019, previously called "A Stratified Approach to Robustness for Randomly Smoothed Classifiers")
17 stars
3 watching
1 forks
Language: Python
last commit: about 5 years ago
Linked from 1 awesome list
benedekrozemberczki/awesome-decision-tree-papersRelated projects:
| Repository | Description | Stars |
|---|---|---|
 hendrycks/robustness | Evaluates and benchmarks the robustness of deep learning models to various corruptions and perturbations in computer vision tasks. | 1,022 |
 borealisai/advertorch | A toolbox for researching and evaluating robustness against attacks on machine learning models | 1,308 |
 robustbench/robustbench | A standardized benchmark for measuring the robustness of machine learning models against adversarial attacks | 667 |
 max-andr/provably-robust-boosting | Provides provably robust machine learning models against adversarial attacks | 50 |
 eth-sri/diffai | Trains neural networks to be provably robust against adversarial examples using abstract interpretation techniques. | 218 |
 thunlp/openattack | A Python toolkit for generating adversarial examples to test the robustness of natural language processing models | 689 |
 aka-discover/ccmba_cvpr23 | Improving semantic segmentation robustness to motion blur using custom data augmentation techniques | 5 |
 edisonleeeee/greatx | A toolbox for graph reliability and robustness against noise, distribution shifts, and attacks. | 83 |
 madrylab/robustness | A library for training and evaluating neural networks with a focus on adversarial robustness. | 918 |
 chenhongge/robusttrees | An implementation of robust decision tree based models against adversarial examples using the XGBoost framework. | 67 |
 google-research/robustness_metrics | A toolset to evaluate the robustness of machine learning models | 466 |
 wenshuoguo/robust-fairness-code | A framework for experimenting with robust optimization methods to improve fairness in machine learning models on noisy protected groups. | 6 |
 illidanlab/fedrbn | An implementation of Federated Robustness Propagation in PyTorch to share robustness across heterogeneous federated learning users. | 26 |
 pokaxpoka/rognoisylabel | A Python package for robust inference via generative classifiers for handling noisy labels in machine learning. | 33 |
 sww9370/rocbert | A pre-trained Chinese language model designed to be robust against maliciously crafted texts | 15 |