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bflc-demo

This project proposes a decentralized federated learning framework based on blockchain, that is, a Block-chain-based Federated Learning framework with Committee consensus (BFLC). Without a centralized server, the framework uses blockchain for the global model storage and the local model update exchange.

biscotti

A ledger for private and secure peer to peer machine learning

chatgpt-on-wechat

cryptozombies-lesson-code

cryptozomebie lesson code

datapoisoning_fl

Code for Data Poisoning Attacks Against Federated Learning Systems

easyfl

An easy-to-use federated learning platform

fate

An Industrial Grade Federated Learning Framework

fedbn

[ICLR'21] FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

federated

A framework for implementing federated learning

fedl

FEDL-Federated Learning algorithm using TensorFlow (Transaction on Networking 2021)

fedml

FedML - The federated learning and analytics library enabling secure and collaborative machine learning on decentralized data anywhere at any scale. Supporting large-scale cross-silo federated learning, cross-device federated learning on smartphones/IoTs, and research simulation. MLOps and App Marketplace are also enabled (https://open.fedml.ai).

flower

Flower - A Friendly Federated Learning Framework

go-taireum

Taireum 一种兼容以太坊的企业级分布式账本与智能合约平台

heterofl-computation-and-communication-efficient-federated-learning-for-heterogeneous-clients

HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

niid-bench

Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)

pfl-non-iid

Personalized federated learning simulation platform with Non-IID and unbalanced dataset

practicing-federated-learning

pysyft

Data science on data without acquiring a copy

splitavg

This repository includes the official project of SplitAVG, from our paper "SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging".

swarm-learning

A simplified library for decentralized, privacy preserving machine learning