An Open Framework for Federated Learning.

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

PyTorch implementation of FedNova (NeurIPS 2020), and a class of federated learning algorithms, including FedAvg, FedProx.

⚔️ Blades: A Unified Benchmark Suite for Attacks and Defenses in Federated Learning

(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…

NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference

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

Three implementations of FedAvg: numpy, pytorch and tensorflow federated.

Apply Federated Learning and Deep Learning (Deep Auto-encoder) to detect abnormal data for IoT devices.

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.

Simple implementation of FedAvg, a Federated Learning algorithm.

The implementation of FedAvg based on pytorch .

PyTorch implementation of federated learning on MNIST

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"

An FL algorithm inspired by FedGMA

Centralized Federated Learning using WebSockets and TensorFlow

Federated Learning with flower and pytorch using a metaheuristic based on the beta distribution