Found by comparing what the projects do, not just their names.
Federated Learning Framework
A project that proposes a novel federated learning approach to address the issue of incomplete information in personalized machine learning models
Federated Learning Library
An implementation of Personalized Federated Learning with Gaussian Processes using Python.
Federated Learning Framework
A framework that enables federated learning across multiple datasets while optimizing model performance with record similarities.
FL framework
A PyTorch-based framework for Federated Learning experiments
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 non-IID federated learning via neural propagation
Federated Learning Suite
An implementation of federated learning and split learning techniques with PyTorch on the HAM10000 dataset
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 implementation of a heterogenous federated learning framework using model distillation.
Federated Learning
This project enables personalized federated learning with inferred collaboration graphs to improve the performance of machine learning models on non-IID (non-independent and identically distributed) datasets.
Federated learning frameworks
An implementation of various federated learning algorithms with a focus on communication efficiency, robustness, and fairness.
Federated Learning Framework
A framework for collaborative distributed machine learning in enterprise environments.
Federated Learning System
A PyTorch implementation of an attack-tolerant federated learning system to train robust local models against malicious attacks from adversaries.
Federated Learning Algorithms
Implementation of various federated learning algorithms to mitigate dimensional collapse in heterogeneous federated learning environments
Federated Learning Framework
Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models.