Category: A2; Team Name: AP; Dataset: DAWN#220
Category: A2; Team Name: AP; Dataset: DAWN#220AbhijeetDutta1 wants to merge 18 commits intogeometric-intelligence:mainfrom
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Dear Participants,
Thank you for your contribution.
We noticed that the configs/dataset/hypergraph/DAWN folder has been added directly to the repository in this pull request.
As noted in our challenge guidelines, we avoid committing large dataset files directly to the repository. This practice is crucial for keeping the repository size manageable for all contributors and ensuring that we are referencing the most up-to-date, original open-source data.
Required Action: Please remove the configs/dataset/hypergraph/DAWN folder from your submission. Instead, please implement a script or update the data-loading pipeline to automatically download this dataset from its open-source platform when the code is run or set up.
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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! |
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Disk Space Issue for Docs. Disregard recent changes and refer to the last commit that passed all |
Authors:
AbhijeetDutta1 abhiduttaca@gmail.com
liupa-trick patrick_liu@ucsb.edu
Checklist
Description
This pull request adds support for the DAWN (Drug Abuse Warning Network) dataset, a temporal higher-order network representing sequences of timestamped simplices, where each simplex corresponds to the set of drugs used during a patient’s emergency department visit. The dataset spans eight years (2004–2011), with timestamps recorded quarterly.
References:
Austin R. Benson, Rediet Abebe, Michael T. Schaub, Ali Jadbabaie, and Jon Kleinberg. Simplicial closure and higher-order link prediction. Proceedings of the National Academy of Sciences (PNAS), 2018.
Link to Dataset:
https://www.cs.cornell.edu/~arb/data/DAWN/
Cornell Paper on simplicial closure and higher-order link prediction
https://arxiv.org/abs/1802.06916
Issue
Additional context