适合可解释的模型。解释黑匣子机器学习。
differential-privacy 开源项目推荐(782 个)
differential-privacy 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 782 个仓库Google's differential privacy libraries.
A unified framework for privacy-preserving data analysis and machine learning
Master Federated Learning in 2 Hours—Run It on Your PC!
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Training PyTorch models with differential privacy
数据库匿名化和测试数据管理
Diffprivlib: The IBM Differential Privacy Library
Synthetic Data SDK ✨
OpenHuFu is an open-sourced data federation system to support collaborative queries over multi databases with security guarantee.
Benchmark of federated learning. Dedicated to the community. 🤗
Synthetic data generators for structured and unstructured text, featuring differentially private learning.
The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy
The core library of differential privacy algorithms powering the OpenDP Project.
Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)
关于基于DP的联合学习,包括论文和代码,你想要的一切。(机制:拉普拉斯或高斯,数据集:femnist、shakespeare、mnist、cifar-10 和 fashion-mnist。)
Simulate a federated setting and run differentially private federated learning.
Differentially private federated learning: A systematic review (ACM Survey); Adap dp-fl: Differentially private federated learning with adaptive noise (TrustCom'2022)
Simulation framework for accelerating research in Private Federated Learning
Repository for collection of research papers on privacy.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/differential-privacy。
- 该话题在 GitHub 上共有 782 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 2.8 万 Star,覆盖 6 种主要语言,数据更新于 2026-11-06。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。