Open Source · Observability
Awesome Federated Learning Systems
Federated Learning Systems Paper List
Our verdict
We have not reviewed Awesome Federated Learning Systems yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About Awesome Federated Learning Systems
A curated list of academic papers on federated learning systems. Maintained by a community contributor, it organizes research for developers exploring privacy-preserving distributed machine learning.
Best for
Researchers and engineers new to federated learning systems who need a starting point for literature discovery.
Use cases
- Surveying state-of-the-art federated learning system architectures
- Identifying key challenges in communication-efficient distributed training
- Benchmarking papers on client selection and aggregation methods
Notes
75 stars on GitHub. Last updated 2024-02-07.
Pros
- Focused curation saves time on literature review
- Open source and community maintained
- Covers both theoretical and systems papers
Cons
- Low star count suggests limited community adoption
- Only links to papers, no code implementations
- Primarily a reading list, not a deployable tool
Key facts
What we have checked
- GitHub stars
- 75
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Sources
Where this comes from
- github api via nightly crawl, recovered from git history e908f0e3f60ee9a6a9776accb9286b434cdbaebcRegistry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
No changes recorded yet. Releases, price changes and deprecations appear here, with their dates, once we track them for this record.
Pairs with
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