Found by comparing what the projects do, not just their names.
Continual Learning Framework
An implementation of a Continual Federated Learning algorithm using Generative Replay to adapt models to new data distributions.
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 collaborative learning across multiple tasks and datasets in a distributed manner
Federated learning framework
An implementation of Fair and Consistent Federated Learning using Python.
Federated Learning Framework
An implementation of a robust federated learning framework for handling noisy and heterogeneous clients in machine learning.
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 balance competing goals in federated learning by decoupling generic and personalized prediction tasks.
Federated learning framework
An implementation of Federated Continual Learning with Weighted Inter-client Transfer using TensorFlow 2.
Domain adaptation
Improves federated learning performance by incorporating domain knowledge and regularization to adapt models across diverse domains
Clustered Federated Learning Framework
A framework for decentralized collaborative learning across multiple clusters with efficient communication and data management strategies.
Federated Learning
Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data
Federated Learning Framework
An implementation of a personalized federated learning framework with decentralized sparse training and peer-to-peer communication protocol.
Federated learning platform
A decentralized federated learning framework based on blockchain and PyTorch.
Federated Learning Framework
Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models.
Federated Learning Framework
An implementation of a federated learning framework for handling data heterogeneity in decentralized settings