Found by comparing what the projects do, not just their names.
Federated Learning Platform
A comprehensive platform for federated learning, providing an event-driven architecture and flexible customization for various tasks in academia and industry.
Federated Learning Framework
A flexible framework for distributed machine learning where participants train local models and collaboratively optimize them without sharing data
Federated Learning Framework
An open source federated learning framework designed to be secure, scalable and easy-to-use for enterprise environments
Federated learning model
A Python implementation of Personalized Federated Learning with Graph using PyTorch.
Federated Learning Toolkit
Provides tools and APIs for designing, scheduling, and running federated machine learning jobs in a secure and efficient manner.
Federated learning platform
A decentralized federated learning framework based on blockchain and PyTorch.
Federated learning framework
Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions.
Federated Learning Framework
A framework for collaborative distributed machine learning in enterprise environments.
FL framework
Enables the training and validation of machine learning models on distributed datasets in a secure and scalable manner.
Federated learning platform
An easy-to-use platform for federated learning on PyTorch
Federated learner
An adaptive federated learning framework for heterogeneous clients with resource constraints.
Federated Learning Framework
A framework for collaborative learning across multiple tasks and datasets in a distributed manner
Federated learning library
An implementation of federated learning with prototype-based methods across heterogeneous clients
Federated Learning Platform
An end-to-end federated learning workflow platform for managing data and models across multiple parties
Federated learning framework
An implementation of Fair and Consistent Federated Learning using Python.