Flower: A Friendly Federated AI Framework
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Updated
Apr 11, 2025 - Python
Flower: A Friendly Federated AI Framework
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
Benchmark of federated learning. Dedicated to the community. 🤗
The first open Federated Learning framework implemented in C++ and Python.
Low-level Python library used to interact with a Substra network
Galaxy Federated Learning Framework (星际联邦学习框架)
⚔️ Blades: A Unified Benchmark Suite for Attacks and Defenses in Federated Learning
HeFlwr: Federated Learning for Heterogeneous Devices
Advanced Privacy-Preserving Federated Learning framework
Simulation Codes for "Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approach"
An Efficient and Easy-to-use Federated Learning Framework.
Nerlnet is a framework for research and development of distributed machine learning models on IoT
[ICLR2023] Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning (https://arxiv.org/abs/2210.00226)
A flexible, modular, and easy to use library to facilitate federated learning research and development in healthcare settings
NEBULA: A Platform for Decentralized Federated Learning
Federated learning with homomorphic encryption enables multiple parties to securely co-train artificial intelligence models in pathology and radiology, reaching state-of-the-art performance with privacy guarantees.
🔨 A Flexible Federated Learning Simulator for Heterogeneous and Asynchronous.
FedRay: a Research Framework for Federated Learning based on Ray
Federated Learning (FL) experiment simulation in Python.
Simulation Codes for “Relay-Assisted Cooperative Federated Learning”
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