BorealisAI / private-data-generation
A toolbox for differentially private data generation
☆129Updated last year
Related projects ⓘ
Alternatives and complementary repositories for private-data-generation
- ☆32Updated last year
- Benchmarking synthetic data generation methods.☆262Updated this week
- ☆39Updated last year
- Differentially Private (tabular) Generative Models Papers with Code☆43Updated 4 months ago
- Source code of paper "Differentially Private Generative Adversarial Network"☆67Updated 5 years ago
- Differentially-private Wasserstein GAN implementation in PyTorch☆27Updated 5 years ago
- Generating Tabular Synthetic Data using State of the Art GAN architecture☆76Updated 4 years ago
- A library for running membership inference attacks against ML models☆139Updated last year
- Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data☆33Updated 5 years ago
- ☆12Updated 3 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆267Updated 11 months ago
- Evaluate real and synthetic datasets against each other☆80Updated this week
- An implementation of the tools described in the paper entitled "Graphical-model based estimation and inference for differential privacy"☆93Updated this week
- Metrics to evaluate quality and efficacy of synthetic datasets.☆212Updated this week
- Supplemental Material for the ESANN 2019 Submission "Preserving privacy using synthetic data models and applications in health informatic…☆19Updated 4 years ago
- Differentially Private Conditional Generative Adversarial Network☆30Updated 3 years ago
- Official git for "CTAB-GAN: Effective Table Data Synthesizing"☆81Updated 10 months ago
- [NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*…☆30Updated 3 years ago
- Repository for the results of my master thesis, about the generation and evaluation of synthetic data using GANs☆42Updated last year
- Python package to create adversarial agents for membership inference attacks againts machine learning models☆47Updated 5 years ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆34Updated 3 years ago
- Differentially Private Optimization for PyTorch 👁🙅♀️☆184Updated 4 years ago
- Generative adversarial training for generating synthetic tabular data.☆282Updated last year
- Analytic calibration for differential privacy with Gaussian perturbations☆44Updated 6 years ago
- Differentially Private Synthetic Data Generation [DP-SDG] - Experimental Setups & Knowledge Base - WORK IN PROGRESS☆11Updated 2 years ago
- Algorithms for Privacy-Preserving Machine Learning in JAX☆89Updated 5 months ago
- PrivGAN: Protecting GANs from membership inference attacks at low cost☆31Updated 5 months ago
- ☆23Updated 10 months ago
- A Unified Framework for Quantifying Privacy Risk in Synthetic Data according to the GDPR☆72Updated 4 months ago