JuliaGraphs / JuliaGraphs/GraphNeuralNetworks.jl
GCNConv implementation is too complicated
Open
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 308
- Forks
- 74
- Avg merge
- 3d 6h
- Merged PRs (30d)
- 2
Description
One possibility in order to simplify the implementation is to incorporate the normalization into the edge weights.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue does not name a file, test, or entry point for the GCNConv implementation. First identify where GCNConv and its normalization are implemented, then establish the intended simplified design and tests needed to show that normalization through edge weights preserves the expected behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100