stefanrmmr / differentially_private_synthetic_dataLinks
Differentially Private Synthetic Data Generation [DP-SDG] - Experimental Setups & Knowledge Base - WORK IN PROGRESS
☆12Updated 3 years ago
Alternatives and similar repositories for differentially_private_synthetic_data
Users that are interested in differentially_private_synthetic_data are comparing it to the libraries listed below
Sorting:
- A toolbox for differentially private data generation☆130Updated 2 years ago
- Generating Tabular Synthetic Data using State of the Art GAN architecture☆82Updated 5 years ago
- ☆40Updated 3 years ago
- Software for evaluating the quality of synthetic data compared with real data.☆33Updated 9 months ago
- ☆38Updated 2 years ago
- Differentially Private (tabular) Generative Models Papers with Code☆54Updated last year
- Official git for "CTAB-GAN: Effective Table Data Synthesizing"☆95Updated last year
- Differentially-private transformers using HuggingFace and Opacus☆145Updated last year
- The privML Privacy Evaluator is a tool that assesses ML model's levels of privacy by running different attacks on it.☆18Updated 4 years ago
- The HyFed framework provides an easy-to-use API to develop federated, privacy-preserving machine learning algorithms.☆18Updated 3 months ago
- Privacy Preserving Machine Learning (Manning Early Access Program)☆33Updated 3 years ago
- nbsynthetic is simple and robust tabular synthetic data generation library for small and medium size datasets☆69Updated 2 years ago
- A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.☆242Updated this week
- A Simulator for Privacy Preserving Federated Learning☆96Updated 4 years ago
- Evaluate real and synthetic datasets against each other☆92Updated 5 months ago
- pyCANON is a Python library and CLI to assess the values of the parameters associated with the most common privacy-preserving techniques.☆47Updated 2 weeks ago
- Official GitHub for CTAB-GAN+☆84Updated last year
- Tools and service for differentially private processing of tabular and relational data☆288Updated 4 months ago
- Private Evolution: Generating DP Synthetic Data without Training [ICLR 2024, ICML 2024 Spotlight]☆109Updated 2 months ago
- Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data☆34Updated 7 years ago
- A library providing general-purpose tools for estimating discrete distributions from noisy observations of their marginals.☆110Updated this week
- A curated list of awesome resources for creating synthetic data☆44Updated 3 years ago
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆25Updated 6 years ago
- Benchmarking synthetic data generation methods.☆289Updated this week
- Federated Learning Demo in Python using Socket Programming☆89Updated last year
- ☆23Updated 3 years ago
- A library for running membership inference attacks against ML models☆152Updated 3 years ago
- tableGAN is a synthetic data generation technique (Data Synthesis based on Generative Adversarial Networks paper) based on Generative Ad…☆153Updated 6 years ago
- Implementation of local differential privacy mechanisms in Python language.☆29Updated 3 years ago
- Course Material for the Tutorial on Privacy Enhancing Technologies and PPML☆13Updated 4 years ago