Statistics for topic federated-learning

Flower: A Friendly Federated AI Framework

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on a...

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

An Industrial Grade Federated Learning Framework

[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification

The implementation of FedAvg based on pytorch.

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

Benchmark of federated learning. Dedicated to the community. 🤗

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

[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification

Flower: A Friendly Federated AI Framework

A curated list of references for MLOps

An Industrial Grade Federated Learning Framework

Master Federated Learning in 2 Hours—Run It on Your PC!

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of Vehicles

Nerlnet is a framework for research and development of distributed machine learning models on IoT

FedML for Autonomous Driving (AD), Intelligent Transportation Systems (ITS), Connected and Automated Vehicles (CAV)

A Git-like Version Control File System for AI & Data Product Management.

🎓 Automatically Update Some Fields Papers Daily using Github Actions (Update Every 12th hours)

Flower: A Friendly Federated AI Framework

A unified framework for privacy-preserving data analysis and machine learning

A curated list of references for MLOps

An Industrial Grade Federated Learning Framework

Master Federated Learning in 2 Hours—Run It on Your PC!

Selective Aggregation for Low-Rank Adaptation in Federated Learning [ICLR 2025]

The implementation of FedAvg based on pytorch.

Kuscia(Kubernetes-based Secure Collaborative InfrA) is a K8s-based privacy-preserving computing task orchestration framework.

Source code for the paper "Joint Class-Balanced Client Selection and Bandwidth Allocation for Cost-Efficient Federated Learning in Mobile Edge Computing Networks".

Simple implementation of FedAvg, a Federated Learning algorithm.

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.

HeFlwr: Federated Learning for Heterogeneous Devices

✨✨A curated list of latest advances on Large Foundation Models with Federated Learning

Source code for the paper "Joint Class-Balanced Client Selection and Bandwidth Allocation for Cost-Efficient Federated Learning in Mobile Edge Computing Networks".

NEBULA: A Platform for Decentralized Federated Learning

Flower: A Friendly Federated AI Framework

A curated list of references for MLOps

Master Federated Learning in 2 Hours—Run It on Your PC!

Perform data science on data that remains in someone else's server

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

Source code for the paper "Joint Class-Balanced Client Selection and Bandwidth Allocation for Cost-Efficient Federated Learning in Mobile Edge Computing Networks".

The implementation of FedAvg based on pytorch.

Federated learning framework made by researchers for researchers :)

(CVPR 2024) Communication-Efficient Federated Learning with Accelerated Client Gradient

CVPR 2024 accepted paper, An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning