https://github.com/bstee615/gnn-tutorial
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- Host: GitHub
- Owner: bstee615
- License: cc0-1.0
- Default Branch: master
- Size: 84.3 MB
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# A Practical Guide to Graph Neural Networks
This repository contains the code for the extended examples in the paper ["A Practical Guide to Graph Neural Networks"](https://arxiv.org/abs/2010.05234).
If using the code here, or referencing the paper, please use the following bibtex citation entry for our preprint.
```
@misc{ward2020practical,
title={A Practical Guide to Graph Neural Networks},
author={Isaac Ronald Ward and Jack Joyner and Casey Lickfold and Yulan Guo and Mohammed Bennamoun},
year={2020},
eprint={2010.05234},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
```
## Folder structure
```
.
html # Exported .html files of the notebooks
notebooks # The .ipynb files of the example code
.gitignore
env.yml # The conda environment dependencies file
LICENSE
README.md
```
## Running on your own computer
Although Jupyter notebooks (```notebooks/```) and exported HTML files (```html/```) have been included in this repository for ease of viewing and sharing, you may still want to clone this repository and run / modify the code yourself.
To do this, use a conda-based package manager and install dependencies from the file ```env.yml``` .yml file. Do this using the following command (or similar):
```
conda env create -f env.yml
```
Activate this environment and run the ```jupyter notebook``` command.
This code has been confirmed to work with Conda 4.10.3.
Owner
- Name: Benjamin Steenhoek
- Login: bstee615
- Kind: user
- Website: benjijang.com
- Repositories: 12
- Profile: https://github.com/bstee615
3rd year PhD student @ ISU. Interests and research: deep learning, program analysis