civisanalytics / dpwgan
Differentially-private Wasserstein GAN implementation in PyTorch
☆27Updated 4 years ago
Related projects: ⓘ
- Source code of paper "Differentially Private Generative Adversarial Network"☆66Updated 5 years ago
- Differentially Private Conditional Generative Adversarial Network☆29Updated 2 years ago
- Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data☆32Updated 5 years ago
- Differentially private release of semantic rich data☆35Updated 3 years ago
- A TensorFlow (Python 3) implementation of a differentially-private-GAN.☆19Updated 4 years ago
- Implementation of a differentially private generative adversarial network.☆10Updated 5 years ago
- Official implementation of "GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators" (NeurIPS 2020)☆65Updated last year
- simple Differential Privacy in PyTorch☆48Updated 4 years ago
- A toolbox for differentially private data generation☆127Updated last year
- A library for running membership inference attacks against ML models☆137Updated last year
- [NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*…☆30Updated 2 years ago
- SAP Security research sample code and tutorials for generating differentially private synthetic datasets using generative deep learning m…☆23Updated 6 months ago
- A simple wrapper for the PATE analysis for Differential Privacy by Papernot, Song et al.☆9Updated 4 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆29Updated 2 years ago
- Differentially Private (tabular) Generative Models Papers with Code☆41Updated 2 months ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆129Updated last year
- Code for Auditing DPSGD☆30Updated 2 years ago
- Algorithms for Privacy-Preserving Machine Learning in JAX☆87Updated 3 months ago
- autodp: A flexible and easy-to-use package for differential privacy☆260Updated 9 months ago
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆64Updated 7 months ago
- ☆16Updated last year
- Analytic calibration for differential privacy with Gaussian perturbations☆44Updated 5 years ago
- ☆77Updated 2 years ago
- Python package to create adversarial agents for membership inference attacks againts machine learning models☆46Updated 5 years ago
- ☆39Updated last year
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆38Updated 5 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆41Updated 2 years ago
- Differentially Private Optimization for PyTorch 👁🙅♀️☆183Updated 4 years ago
- Official implementation of "GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models" (CCS 2020)☆46Updated 2 years ago
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆23Updated 5 years ago