Found by comparing what the projects do, not just their names.
Federated Learning
Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data
Federated Learning Framework
Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models.
Federated learning framework
Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions.
Federated learning library
An implementation of federated learning with prototype-based methods across heterogeneous clients
Federated learning model
A Python implementation of Personalized Federated Learning with Graph using PyTorch.
Federated Learning Framework
A framework for collaborative distributed machine learning in enterprise environments.
Federated Learning Framework
A framework for collaborative learning across multiple tasks and datasets in a distributed manner
Federated Active Learning Framework
An implementation of federated active learning with a novel sampling strategy to improve performance on decentralized machine learning tasks
Federated Learning Framework
Evaluates various methods for federated learning on different models and tasks.
Federated learning framework
An implementation of Fair and Consistent Federated Learning using Python.
Federated learning framework
An implementation of a federated learning method to optimize multiple models simultaneously while maintaining user privacy.
Heterogeneity fixer
Combating heterogeneity in federated learning by combining adversarial training with client-wise slack during aggregation
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 heterogeneous federated learning with parallel edge and server computation
Federated optimizer
An optimization framework designed to address heterogeneity in federated learning across distributed networks