An open framework for Federated Learning.
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Updated
Jun 1, 2024 - Jupyter Notebook
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 Byzantine Attacks and Defenses in Federated Learning
(NeurIPS 2022) Official Implementation of "Preservation of the Global Knowledge by Not-True Distillation in Federated Learning"
Apply Federated Learning and Deep Learning (Deep Auto-encoder) to detect abnormal data for IoT devices.
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…
Simple implementation of FedAvg, a Federated Learning algorithm.
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.
Three implementations of FedAvg: numpy, pytorch and tensorflow federated.
PyTorch implementation of federated learning on MNIST
This repository contains all the implementation of different papers on Federated Learning
Comparison of FedAvg and FedDyn as a final project for the Advance Machine Learning course at Politecnico di Torino
NAACL '24 (Demo) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference
Centralized Federated Learning using WebSockets and TensorFlow
The implementation of FedAvg based on pytorch .
Federated Learning for Swarm Robotics
Decentralized (P2P) Federated Learning implementation using libp2p JavaScript
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