Found by comparing what the projects do, not just their names.
Federated Prompt Algorithm
An algorithm for learning federated visual prompts in null space to improve MRI reconstruction performance on limited local data and reduced communication costs
Federated learning for MRI
Improves deep learning-based magnetic resonance image reconstruction using federated learning and multi-institutional collaboration
Federated learner
An implementation of federated learning algorithm for image classification
Federated learner
Implementation of federated learning algorithms for distributed machine learning on private client data
FedFR framework
An open-source software framework for jointly optimizing face recognition models in federated learning settings.
Federated Learning Framework
Personalized Subgraph Federated Learning framework for distributed machine learning
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 system
An implementation of Fast Federated Learning under device unavailability for minimizing latency and achieving optimal convergence rates
Federated learning framework
Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions.
Feature sharing
An approach to mitigating data heterogeneity in federated learning by sharing partial features of the data.
Federated Optimization Library
This code repository provides an implementation of Federated Composite Optimization for decentralized machine learning
Federated Learning framework
An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources.
Federated learning library
An implementation of federated learning with prototype-based methods across heterogeneous clients
Federated Image Segmentation Framework
This project presents a framework for federated domain generalization in medical image segmentation using continuous frequency space and episodic learning.
Federated Learning
Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data