Datasets:
Tasks:
Graph Machine Learning
Modalities:
Text
Formats:
text
Size:
10K - 100K
ArXiv:
Tags:
art
License:
File size: 1,662 Bytes
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---
size_categories:
- 1K<n<10K
task_categories:
- graph-ml
tags:
- art
license: cc
---
## Dataset Information
| # Nodes | # Edges | # Features |
|:-------:|:-------:|:----------:|
| 2,277 | 36,101 | 2,325 |
## Usage
```python
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="SauravMaheshkar/Chameleon", filename="processed/chameleon.bin", local_dir="./data/", repo_type="dataset")
dataset, _ = dgl.load_graphs("./data/processed/chameleon.bin")
```
Thank you [@severo](https://huggingface.co/severo) for helping me [figure out the usage](https://discuss.huggingface.co/t/can-i-use-a-pickle-file-with-the-data-files-argument-with-datasets/72189/2?u=sauravmaheshkar).
## 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}
}
``` |