awesome-federated-computing
github.com/tushar-semwal/awesome-federated-computing ↗:books: :eyeglasses: A collection of research papers, codes, tutorials and blogs on Federated Computing/Learning.
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BlogsSurvey PapersResearch PapersLibraries/FrameworksTutorialsDatasetsProjects
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Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
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Installation instructions →What's inside
Research Papers
- A Bayesian Federated Learning Framework with Multivariate Gaussian Product2021
- Accelerating DNN Training in Wireless Federated Edge Learning System2019
- Accelerating DNN Training in Wireless Federated Edge Learning System2020
- Adaptive Federated Learning in Resource Constrained Edge Computing Systems2019
- Agnostic Federated Learning2019
- A Performance Evaluation of Federated Learning Algorithms2018
Survey Papers
- Advances and Open Problems in Federated Learning
- Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
- Federated Learning: Challenges, Methods, and Future Directions
- Federated Learning in Mobile Edge Networks: A Comprehensive Survey
- Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
- Federated Machine Learning: Concept and Applications
Blogs
- An Introduction to Federated Learning
- Federated Learning: Collaborative Machine Learning without Centralized Training Data
- Federated learning: Distributed machine learning with data locality and privacy
- Federated Learning for Wake Word Detection
- Federated Learning: The Future of Distributed Machine Learning
- Learn to adapt Flower for your use-case
Libraries/Frameworks
- Flower
A friendly federated learning research framework.
- Industrial Federated Learning Framework
- OpenFL
An open-source framework for Federated Learning on top of TF/PyTorch/etc.
- Paddle Federated Learning
Federated Deep Learning in PaddlePaddle.
- PySyft - Github
The PyTorch based library.
- PyTorch Federated Learning - Github
Github
Showing a sample of 120 resources. View the full list on GitHub →