SAP-archive / security-research-differentially-private-generative-modelsLinks
SAP Security research sample code and tutorials for generating differentially private synthetic datasets using generative deep learning models
☆24Updated last year
Alternatives and similar repositories for security-research-differentially-private-generative-models
Users that are interested in security-research-differentially-private-generative-models are comparing it to the libraries listed below
Sorting:
- Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data☆33Updated 6 years ago
- A toolbox for differentially private data generation☆131Updated 2 years ago
- ☆16Updated 5 years ago
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆25Updated 6 years ago
- Differentially private release of semantic rich data☆35Updated 4 years ago
- Source code of paper "Differentially Private Generative Adversarial Network"☆70Updated 6 years ago
- Differentially-private Wasserstein GAN implementation in PyTorch☆28Updated 5 years ago
- This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"☆27Updated 3 years ago
- Python package to create adversarial agents for membership inference attacks againts machine learning models☆46Updated 6 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated last year
- This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.☆63Updated 6 years ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆33Updated 4 years ago
- Privacy-preserving generative deep neural networks support clinical data sharing☆106Updated 6 years ago
- A concise primer on Differential Privacy☆29Updated 5 years ago
- An implementation of Wasserstein Fair Classification, a conference paper submitted to UAI 2019.☆23Updated 5 years ago
- Fair Empirical Risk Minimization (FERM)☆37Updated 5 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆45Updated 3 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆276Updated last year
- A TensorFlow (Python 3) implementation of a differentially-private-GAN.☆20Updated 5 years ago
- Federated Principal Component Analysis Revisited!☆43Updated 3 years ago
- [NeurIPS 2020] Simple and practical private mean and covariance estimation.☆36Updated 5 years ago
- A library for running membership inference attacks against ML models☆150Updated 2 years ago
- Course Material for the Tutorial on Privacy Enhancing Technologies and PPML☆13Updated 3 years ago
- Differentially Private Conditional Generative Adversarial Network☆31Updated 4 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …☆103Updated 5 years ago
- Code for fast dpsgd implementations in JAX/TF☆59Updated 3 years ago
- ☆40Updated 2 years ago
- ☆37Updated 7 years ago
- ☆80Updated 3 years ago