Category: A1; Team name: Tlaloc; Dataset: WS1000_gamma

[Rubiel1]

Checklist

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

Description

We implement the WS1000-Gamma dataset introduced in: Katsman, I., Lou, E., & Gilbert, A. (2024). Revisiting the Necessity of Graph Learning and Common Graph Benchmarks. https://arxiv.org/abs/2412.06173

We use the task: classification, when 'y' is distance from node to root. The original paper implements edge prediction instead.

Issue

This dataset is important, since it was used as an example in which (for edge prediction) a MLP can do better than graph NN.

Additional context

The next step will be to add the task of edge prediction. Which will be an independent pull request, and perhaps by someone else.

[levtelyatnikov]

Dear Participants,

This is a final reminder regarding the upcoming challenge deadline.

📅 Deadline: Tomorrow, 25th November 2025

✅ Critical Requirement: Please ensure your branch is passing all CI/CD tests.

If you have any pending changes, please push them and verify your build status as soon as possible.

Good luck!