securefederatedai/openfl

An open framework for Federated Learning.

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Lee-Gihun/FedNTD

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

Language: Python - Size: 364 KB - Last synced: about 1 month ago - Pushed: over 1 year ago - Stars: 68 - Forks: 14

shyam671/Federated-Learning

Language: Jupyter Notebook - Size: 11.4 MB - Last synced: 3 months ago - Pushed: almost 2 years ago - Stars: 14 - Forks: 3

vaseline555/Federated-Learning-in-PyTorch

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

Language: Python - Size: 148 KB - Last synced: 7 months ago - Pushed: 7 months ago - Stars: 279 - Forks: 69

BThameur/FL-for-Smart-Healthcare

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

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gautamHCSCV/Federated-Learning-Methods-Comparison

We utilize the Adversarial Model Perturbations (AMP) regularizer to regularize clients’ models. The AMP regulzaizer is based on perturbing the model parameters so as to get a more generalized model. The claim of AMP regularizer is to reach flat minima and therefore is expected to reach flat minima in FL settings as well.

Language: Python - Size: 1.22 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

Turningl/fedavg_pytorch

federated learning with opacus

Language: Python - Size: 43.9 KB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 3 - Forks: 0

c-gabri/Federated-Learning-PyTorch

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 provided

Language: Python - Size: 126 MB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 41 - Forks: 9

ayushm-agrawal/Federated-Learning-Implementations

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

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ysyisyourbrother/Federated-Learning-Research

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.

Language: Python - Size: 43 KB - Last synced: about 1 year ago - Pushed: almost 2 years ago - Stars: 16 - Forks: 1

ki-ljl/FedProx-PyTorch

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

Language: Python - Size: 23 MB - Last synced: about 1 year ago - Pushed: almost 2 years ago - Stars: 47 - Forks: 9