Skip to content

Track: Track1; Team name: kxdenz; Model: ESC-GNN - #419

Open
KadenZheng wants to merge 1 commit into
geometric-intelligence:mainfrom
KadenZheng:tdl26-track1-esc-gnn
Open

KadenZheng wants to merge 1 commit into
geometric-intelligence:mainfrom
KadenZheng:tdl26-track1-esc-gnn

Conversation

@KadenZheng

@KadenZheng KadenZheng commented Aug 2, 2026 •

Copy link
Copy Markdown

Checklist

  • My pull request has a clear and explanatory title.
  • My pull request passes the Linting test.
  • I added appropriate unit tests and I made sure the code passes all unit tests.
  • My PR follows PEP8 guidelines.
  • My code is properly documented, using numpy docs conventions, and I made sure the documentation renders properly.
  • I linked to issues and PRs that are relevant to this PR.

Publication

Zuoyu Yan et al., “An Efficient Subgraph GNN with Provable Substructure Counting Power,” KDD 2024.

https://doi.org/10.1145/3637528.3671731

Integrate paper-aligned ESC structural encoding with TopoBench and include the official GraphUniverse evaluation artifact and regression coverage.
@KadenZheng

KadenZheng commented Aug 2, 2026 •

Copy link
Copy Markdown
Author

Could a maintainer please apply the required track-1-gnn label for this? Seems like I don't have perms!

Also, all GH Actions checks passed but it seems like the Codecov step couldn't publish because the fork-PR upload was rejected with "Token required - not valid tokenless upload." Sorry for the trouble - could a maintainer please also confirm the coverage requirement or rerun Codecov with the repository token?

Thank you!

@gbg141 gbg141 added the track-1-gnn 2026 Topological Deep Learning Challenge -- Track 1 GNNs label Aug 2, 2026

This branch has not been deployed

No deployments
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

track-1-gnn 2026 Topological Deep Learning Challenge -- Track 1 GNNs

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants