[NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*, Boxin Wang*, Zhuolin Yang, Bhavya Kailkhura, Aston Zhang, Carl A. Gunter, Bo Li
☆30Oct 26, 2021Updated 4 years ago
Alternatives and similar repositories for G-PATE
Users that are interested in G-PATE are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Differentially Private Conditional Generative Adversarial Network☆31Oct 12, 2021Updated 4 years ago
- Implementation of a differentially private generative adversarial network.☆11Nov 20, 2018Updated 7 years ago
- ☆12Jun 17, 2022Updated 3 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆46Nov 29, 2021Updated 4 years ago
- ☆16Mar 30, 2023Updated 3 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Improved DP-SGD for optimizing☆20Mar 23, 2019Updated 7 years ago
- ☆24Apr 29, 2022Updated 4 years ago
- Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data☆34Dec 8, 2018Updated 7 years ago
- This repository contains all public data, python scripts, and documentation relating to NIST Public Safety Communications Research Divisi…☆12Nov 22, 2022Updated 3 years ago
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆76Feb 15, 2024Updated 2 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆280Dec 5, 2023Updated 2 years ago
- CaPC is a method that enables collaborating parties to improve their own local heterogeneous machine learning models in a setting where b…☆24Mar 16, 2022Updated 4 years ago
- A implementation of DCGAN (Deep Convolutional Generative Adversarial Networks) for CIFAR10 image☆18Jan 31, 2018Updated 8 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆32Apr 25, 2022Updated 4 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- A TensorFlow (Python 3) implementation of a differentially-private-GAN.☆20Feb 21, 2020Updated 6 years ago
- Source code of paper "Differentially Private Generative Adversarial Network"☆72Nov 29, 2018Updated 7 years ago
- ☆79May 28, 2022Updated 3 years ago
- Local Differential Privacy for Federated Learning☆19Oct 24, 2022Updated 3 years ago
- Differentially Private Diffusion Models☆106Dec 26, 2023Updated 2 years ago
- Differentially Private (tabular) Generative Models Papers with Code☆54Jul 2, 2024Updated last year
- Differentially private release of semantic rich data☆35Jun 17, 2021Updated 4 years ago
- On Robustness of Neural Ordinary Differential Equations☆11Oct 12, 2021Updated 4 years ago
- "Stochasticity in Neural ODEs: An Empirical Study". Experiments from the paper☆13Apr 27, 2020Updated 6 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- 同态加密☆21Dec 29, 2021Updated 4 years ago
- ☆13Apr 12, 2022Updated 4 years ago
- Differentially-private transformers using HuggingFace and Opacus☆147Aug 28, 2024Updated last year
- Targeted Data Generation with Large Language Models☆20Jun 25, 2024Updated last year
- DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.☆37May 30, 2025Updated 11 months ago
- Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)☆48Aug 18, 2022Updated 3 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆136Dec 8, 2022Updated 3 years ago
- This repo implements several algorithms for learning with differential privacy.☆110Dec 15, 2022Updated 3 years ago
- ☆13Oct 24, 2021Updated 4 years ago
- Proton VPN Special Offer - Get 70% off • AdSpecial partner offer. Trusted by over 100 million users worldwide. Tested, Approved and Recommended by Experts.
- ☆12Dec 22, 2025Updated 4 months ago
- PyTorch implementation for OCT-GAN Neural ODE-based Conditional Tabular GANs (WWW 2021)☆15Oct 10, 2022Updated 3 years ago
- The privML Privacy Evaluator is a tool that assesses ML model's levels of privacy by running different attacks on it.☆18Sep 6, 2021Updated 4 years ago
- ☆11May 9, 2022Updated 3 years ago
- Target Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning☆10Jul 2, 2019Updated 6 years ago
- Unified, Simplified, Tight and Fast Privacy Amplification in the Shuffle Model of Differential Privacy☆11Oct 27, 2024Updated last year
- [ICLR'24 Spotlight] DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer☆47May 30, 2024Updated last year