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FedGraph (Federated Graph) is a library built upon PyTorch to easily train Graph Neural Networks (GNNs) under federated (distributed) setting.
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
A unified framework for privacy-preserving data analysis and machine learning
Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)
A trusty face analysis research platform developed by Tencent Youtu Lab
A biblatex implementation of the GB/T7714-2015 bibliography style || GB/T 7714-2015 参考文献著录和标注的biblatex样式包
A cross compiler and standardized benchmarks for fully homomorphic encryption
A library for doing homomorphic encryption operations on tensors
HElib is an open-source software library that implements homomorphic encryption. It supports the BGV scheme with bootstrapping and the Approximate Number CKKS scheme. HElib also includes optimizati…
OpenFHE-Based Examples of Logistic Regression Training using Nesterov Accelerated Gradient Descent
Official Python wrapper for OpenFHE. Current release is v0.8.8 (released on June 25, 2024).
PYthon For Homomorphic Encryption Libraries, perform encrypted computations such as sum, mult, scalar product or matrix multiplication in Python, with NumPy compatibility. Uses SEAL/PALISADE as bac…
Privacy-Preserving Convolutional Neural Networks using Homomorphic Encryption
A mathematical and code introduction to the BFV Homomorphic Encryption scheme.
A Framework for Encrypted Machine Learning in TensorFlow
An easy-to-use federated learning platform
Microsoft SEAL is an easy-to-use and powerful homomorphic encryption library.
Official Implementation of "LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference"
NuCypher fully homomorphic encryption (NuFHE) library implemented in Python
A curated list of awesome TikZ documentations, libraries and resources
Privacy Preserving Federated Learning on a Deep Neural Network
This is the development repository for the OpenFHE library. The current (stable) version is v1.2.0 (released on June 25, 2024).
Homomorphic Encryption and Federated Learning based Privacy-Preserving
Perform data science on data that remains in someone else's server
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)