Reliable-and-Trustworthy-AI-Notebooks
AI protection
Research-focused notebooks on developing robust and secure AI models against adversarial attacks
Reliable and Trustworthy Intelligence AI notebooks from ETH Zurich course taught by Prof. Dr. Martin Vechev
1 stars
2 watching
0 forks
Language: Jupyter Notebook
last commit: almost 5 years agoLinked from 1 awesome list
interpretable-aineural-networksreliable-aitrustworthy-ai
Related projects:
| Repository | Description | Stars |
|---|---|---|
| An implementation of a DeepPoly-based verifier for robustness analysis in deep neural networks | 2 | |
| A toolkit for explaining complex AI models and data-driven insights | 1,641 | |
| An online repository providing resources and information on explainable AI, algorithmic fairness, ML security, and related topics | 107 | |
| Guidelines and resources for the development of responsible AI systems | 17 | |
| Provides Python code and Jupyter Notebooks for a finance book on Artificial Intelligence | 315 | |
| Jupyter notebooks and accompanying resources for teaching computer science fundamentals | 1,315 | |
| Differential machine learning implementation and demonstration notebooks | 138 | |
| An AI-centric extension to JupyterLab Notebooks | 1,861 | |
| A benchmark environment for fully cooperative human-AI performance in a cooking game | 726 | |
| Teaches software developers how to build, deploy, and maintain products with machine-learning models. | 385 | |
| Trains neural networks to be provably robust against adversarial examples using abstract interpretation techniques. | 219 | |
| Provides course materials and code examples for teaching AI art concepts using various machine learning techniques | 567 | |
| This project presents a framework for robust federated learning against backdoor attacks. | 71 | |
| Analyzing and exploring Common Crawl data using Jupyter notebooks to provide insights into webarchiving and internet connections. | 48 | |
| Repository providing example notebooks for Deep Learning applications with TensorFlow and Earth Engine. | 76 |