Welcome to this project, in which I researched the expressiveness of Line Graph Neural Networks! Please find the project report here. With the code in this repository, I obtained the results of the experiment at the end of the report.
| File | Description |
|---|---|
code/main.ipynb |
The main results displayed in the report, as well as the used graph figures, can be found in code/main.ipynb. To run this notebook yourself, follow the procedure in the section 'Running code/main.ipynb' of this file. |
code/dataset.py |
The code in this file was used to preprocess the datasets used in these experiments (i.e. sample subgraphs for link prediction). |
code/experiment.py |
The code in this file was used to train the models. |
code/models.py |
This file contains the model implementations. |
code/utils.py |
This file contains utility functions for the rest of the project. |
| Folder | Description |
|---|---|
code/study |
Contains the TensorBoard logs of the three experiments (subfolder names: PPI-hidden-dim-20, PPI-hidden-dim-52, TwitchEN-hidden-dim-20). |
code/data |
Is supposed to contain the dataset. If you want to run code/main.ipynb yourself, you will need to fill this folder with the right data, as outlined in the next section. |
report |
Contains the TeX code used to generate the report. |
To run code/main.ipynb, you will need to download the datasets from the following link: https://drive.google.com/drive/folders/1KiYGXAuR-3VBO31yu82S8QLrxGLgwc_2?usp=sharing
and create the following folder structure in the code/data folder.
Then, everything should run!
| data
|---- TwitchENDataset
|---- PPIDataset