Found by comparing what the projects do, not just their names.
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 federated learning with partial model personalization
Federated Learning Framework
Personalized Subgraph Federated Learning framework for distributed machine learning
FL framework
Enables the training and validation of machine learning models on distributed datasets in a secure and scalable manner.
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 Framework
A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems.
Federated Learning Framework
A framework for tackling heterogeneity and catastrophic forgetting in federated learning by leveraging cross-correlation and similarity learning
Topology optimizer
A toolkit for optimizing federated learning in cross-silo settings by designing efficient communication topologies
Federated Learning Framework
A framework for federated learning that leverages the neural tangent kernel to address statistical heterogeneity in distributed machine learning.
Federated Learning Framework
A framework for non-IID federated learning via neural propagation
Federated learning model
A Python implementation of Personalized Federated Learning with Graph using PyTorch.
FL framework
A unified framework for improving privacy and reducing communication overhead in distributed machine learning models.
Federated Learning Framework
An implementation of a personalized federated learning framework with decentralized sparse training and peer-to-peer communication protocol.
Federated Learning Framework
Develops a framework to balance competing goals in federated learning by decoupling generic and personalized prediction tasks.
Personalized FL framework
A framework for personalized federated learning that creates dynamic models for each input instance and improves generalizability of global models.