metadata
size_categories:
- 1K<n<10K
task_categories:
- graph-ml
tags:
- art
license: cc
Dataset Information
| # Nodes | # Edges | # Features |
|---|---|---|
| 5,201 | 217,073 | 2,089 |
Usage
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="SauravMaheshkar/pareto-squirrel", filename="processed/squirrel.bin", local_dir="./data/", repo_type="dataset")
dataset, _ = dgl.load_graphs("./data/processed/squirrel.bin")
Thank you @severo for helping me figure out the usage.
Pre-processed as per the official codebase of https://arxiv.org/abs/2210.02016
Citations
@article{ju2023multi,
title={Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization},
author={Ju, Mingxuan and Zhao, Tong and Wen, Qianlong and Yu, Wenhao and Shah, Neil and Ye, Yanfang and Zhang, Chuxu},
booktitle={International Conference on Learning Representations},
year={2023}
}
@article{DBLP:journals/corr/abs-1909-13021,
author = {Benedek Rozemberczki and
Carl Allen and
Rik Sarkar},
title = {Multi-scale Attributed Node Embedding},
journal = {CoRR},
volume = {abs/1909.13021},
year = {2019},
url = {http://arxiv.org/abs/1909.13021},
eprinttype = {arXiv},
eprint = {1909.13021},
timestamp = {Wed, 02 Oct 2019 13:04:08 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-1909-13021.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}