Handy PyTorch implementation of Federated Learning (for your painless research)

PyTorch implementation of FedProx (Federated Optimization for Heterogeneous Networks, MLSys 2020).

(NeurIPS 2022) Official Implementation of "Preservation of the Global Knowledge by Not-True Distillation in Federated Learning"

PyTorch implementation of Federated Learning algorithms FedSGD, FedAvg, FedAvgM, FedIR, FedVC, FedProx and standard SGD, applied to visual classification. Client distributions are synthesized with arbitrary non-identicalness and imbalance (Dirichlet priors). Client systems can be arbitrarily heterogeneous. Several mobile-friendly models are prov…

This repository contains all the implementation of different papers on Federated Learning

An implementation of federated learning research baseline methods based on FedML-core, which can be deployed on real distributed cluster and help researchers to explore more problems existing in real FL systems.

Federated Learning Experiments for Remote Sensing image data using convolution neural networks

(CVPR 2024) Official Implementation of "FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning"

research-based, fully open-source, peer-to-peer gossip learning framework

[L4DC 2025] Controlling Pariticipation in Federated Learning with Feedback

A reliability-driven federated learning framework for multi-label thorax disease classification that simulates collaborative hospital training without sharing raw patient data.

An AI-driven Adaptive Traffic Signal Control System (ATSCS) that replaces static timers with dynamic green-light phases. Utilizes YOLOv8 for real-time vehicle density estimation and multi-class classification, achieving 96.4% mAP. Optimized for low-latency inference (>30 FPS) on edge devices to reduce urban congestion and commuter wait times.

Official implementation of DP-FedSOFIM: differentially private federated learning with second-order Fisher Information Matrix optimization (TMLR 2026, under review)

Experiments of the FL in Healthcare project - MRI images use case - using Flower

Network-Aware Federated Optimisation (NAFO): a 5G-native framework that jointly optimizes wireless channel conditions, differential privacy, and multi-modal healthcare AI. Demonstrates robust federated learning under realistic 3GPP network constraints with AoI-aware dynamics.

Distributed Federated Learning simulation on a 4-node 6G edge network — FedAvg vs FedProx under IID and non-IID traffic distributions | CIFRE PhD thesis preparation — Orange Innovation TREES project

Federated learning platform for privacy-preserving health anomaly detection across hospitals, using LSTM models trained with FedProx. It combines a FastAPI + gRPC orchestrator, Next.js dashboards, an Electron client agent, and Supabase-backed RBAC/realtime analytics with Differential Privacy and optional Homomorphic Encryption.

A fast, extensible federated learning framework built on PyTorch

An implementation of Evolutionary and connectionist hybrid experiments.