Statistics for topic federated-learning

Flower: A Friendly Federated AI Framework

A curated list of references for MLOps

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

Personalized federated learning codebase for research

NVIDIA Federated Learning Application Runtime Environment

ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341

The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients"

Personalized federated learning codebase for research

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

NVIDIA Federated Learning Application Runtime Environment

Flower: A Friendly Federated AI Framework

A curated list of references for MLOps

NVIDIA Federated Learning Application Runtime Environment

A PyTorch Implementation of Federated Learning

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

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

You only need to configure one file to support model heterogeneity. Consistent GPU memory usage for single or multiple clients.

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

I put all my exploration around AI in reproducible notebooks in this repository

ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341

Flower: A Friendly Federated AI Framework

A curated list of references for MLOps

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

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

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

ByzFL: A Python library for robust federated learning, offering Byzantine-resilient aggregators, attack simulations, and ML pipelines for distributed systems. Compatible with PyTorch and NumPy.

NEBULA: A Platform for Decentralized Federated Learning

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

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

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

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

HeFlwr: Federated Learning for Heterogeneous Devices

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

Source code for the paper "Group-based Federated Learning with Cost-efficient Sampling Mechanism in Mobile Edge Computing Networks".

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 :)

Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning

Source code for the paper "Group-based Federated Learning with Cost-efficient Sampling Mechanism in Mobile Edge Computing Networks".