REPOGEO REPORT · LITE
AshwinRJ/Federated-Learning-PyTorch
Default branch master · commit 26eaec40 · scanned 6/28/2026, 8:38:21 PM
GitHub: 1,440 stars · 461 forks
Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface AshwinRJ/Federated-Learning-PyTorch, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Reposition README to clarify its purpose as a research/educational implementation
Why:
CURRENTImplementation of the vanilla federated learning paper : Communication-Efficient Learning of Deep Networks from Decentralized Data.
COPY-PASTE FIXThis repository provides a clear, minimal PyTorch implementation of the vanilla federated learning paper, 'Communication-Efficient Learning of Deep Networks from Decentralized Data,' designed for researchers and students to understand and experiment with the core concepts of federated learning.
- mediumhomepage#2Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIXhttps://github.com/AshwinRJ/Federated-Learning-PyTorch
- lowtopics#3Expand repository topics to include specific experimental setups and purpose
Why:
CURRENTdeep-learning, distributed-computing, federated-learning, python, pytorch
COPY-PASTE FIXdeep-learning, distributed-computing, federated-learning, python, pytorch, mnist, cifar10, non-iid-data, iid-data, research-implementation, educational-resource
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- PySyft · recommended 2×
- Flower · recommended 2×
- TensorFlow Federated · recommended 1×
- OpenFL · recommended 1×
- Ray · recommended 1×
- CATEGORY QUERYHow to train deep learning models efficiently across multiple decentralized data sources?you: not recommendedAI recommended (in order):
- PySyft
- Flower
- TensorFlow Federated
- OpenFL
- Ray
- Horovod
- Substra
AI recommended 7 alternatives but never named AshwinRJ/Federated-Learning-PyTorch. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking a PyTorch framework for communication-efficient federated learning with varied data distributions.you: not recommendedAI recommended (in order):
- FedML
- Flower
- PySyft
- LEAF
- FedProx
AI recommended 5 alternatives but never named AshwinRJ/Federated-Learning-PyTorch. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of AshwinRJ/Federated-Learning-PyTorch?passAI did not name AshwinRJ/Federated-Learning-PyTorch — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts AshwinRJ/Federated-Learning-PyTorch in production, what risks or prerequisites should they evaluate first?passAI named AshwinRJ/Federated-Learning-PyTorch explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo AshwinRJ/Federated-Learning-PyTorch solve, and who is the primary audience?passAI did not name AshwinRJ/Federated-Learning-PyTorch — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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AshwinRJ/Federated-Learning-PyTorch — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite