facebookresearch / privacy_lint
Lint for privacy
☆26Updated 2 years ago
Alternatives and similar repositories for privacy_lint
Users that are interested in privacy_lint are comparing it to the libraries listed below
Sorting:
- Research and experimental code related to Opacus, an open-source library for training PyTorch models with Differential Privacy☆17Updated 7 months ago
- Algorithms for Privacy-Preserving Machine Learning in JAX☆94Updated last month
- A concise primer on Differential Privacy☆29Updated 4 years ago
- Code for Auditing DPSGD☆37Updated 3 years ago
- Privacy Testing for Deep Learning☆204Updated last year
- CaPC is a method that enables collaborating parties to improve their own local heterogeneous machine learning models in a setting where b…☆26Updated 3 years ago
- PyTorch implementation of parity loss as constraints function to realize the fairness of machine learning.☆73Updated 2 years ago
- Secure collaborative training and inference for XGBoost.☆105Updated 2 years ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆34Updated 4 years ago
- Library and experiments for attacking machine learning in discrete domains☆45Updated 2 years ago
- ☆38Updated 2 years ago
- Code for fast dpsgd implementations in JAX/TF☆59Updated 2 years ago
- Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …☆103Updated 5 years ago
- ☆37Updated 3 years ago
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆73Updated last year
- ☆16Updated 5 years ago
- Github pages backend for https://differentialprivacy.org☆26Updated last week
- Statistical Counterexample Detector for Differential Privacy☆28Updated last year
- Privacy-preserving XGBoost Inference☆49Updated 2 years ago
- A codebase that makes differentially private training of transformers easy.☆171Updated 2 years ago
- ☆123Updated 3 years ago
- FedJAX is a JAX-based open source library for Federated Learning simulations that emphasizes ease-of-use in research.☆261Updated last month
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆61Updated 4 years ago
- ☆80Updated 2 years ago
- ☆144Updated 7 months ago
- Credo AI Lens is a comprehensive assessment framework for AI systems. Lens standardizes model and data assessment, and acts as a central …☆47Updated 11 months ago
- Fork of the differential privacy module of TF/models/research☆14Updated 5 years ago
- ☆23Updated last year
- Privacy-Preserving Bandits (MLSys'20)☆22Updated 2 years ago
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆24Updated 5 years ago