REPOGEO REPORT · LITE
vgsatorras/egnn
Default branch main · commit e9ca6c0c · scanned 6/3/2026, 5:43:05 AM
GitHub: 537 stars · 89 forks
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 vgsatorras/egnn, 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
2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highabout#1Add a concise repository description
Why:
COPY-PASTE FIXOfficial PyTorch implementation of E(n)-Equivariant Graph Neural Networks (EGNNs) for models equivariant to rotations, translations, reflections, and permutations, applicable to dynamical systems, representation learning, and molecular properties.
- mediumhomepage#2Add the paper's arXiv link as the repository homepage
Why:
COPY-PASTE FIXhttps://arxiv.org/abs/2102.09844
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.
- e3nn · recommended 2×
- SE(3)-Transformers · recommended 2×
- PyTorch Geometric (PyG) · recommended 1×
- TensorFlow GNN (TF-GNN) · recommended 1×
- DeepMind's Graph Networks library (GraphNets) · recommended 1×
- CATEGORY QUERYHow to implement graph neural networks that are equivariant to geometric transformations?you: not recommendedAI recommended (in order):
- e3nn
- PyTorch Geometric (PyG)
- SE(3)-Transformers
- TensorFlow GNN (TF-GNN)
- DeepMind's Graph Networks library (GraphNets)
- JAX
- Jraph
AI recommended 7 alternatives but never named vgsatorras/egnn. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking PyTorch libraries for building rotation-invariant graph models for molecular dynamics.you: not recommendedAI recommended (in order):
- e3nn
- PyTorch Geometric
- TorchMD-Net
- NequIP
- SE(3)-Transformers
AI recommended 5 alternatives but never named vgsatorras/egnn. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenessfail
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 vgsatorras/egnn?passAI named vgsatorras/egnn explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts vgsatorras/egnn in production, what risks or prerequisites should they evaluate first?passAI named vgsatorras/egnn 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 vgsatorras/egnn solve, and who is the primary audience?passAI named vgsatorras/egnn explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
Drop this badge into the README of vgsatorras/egnn. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
Live preview[](https://repogeo.com/en/r/vgsatorras/egnn)<a href="https://repogeo.com/en/r/vgsatorras/egnn"><img src="https://repogeo.com/badge/vgsatorras/egnn.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
vgsatorras/egnn — 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