MAGPool: Multi-Subspace Attention Graph Pooling

The implementation for paper Multi-Subspace Attention Graph Pooling

Requirements

1. Python==3.7
2. torch
3. torch_scatter
4. torch_geometric
5. matplotlib

Datasets

We used torch_geometric to manage the datasets, it will automatically download the corresponding dataset once you run the code and put it under \data

Run

The main entrance of this project is in main.py.

The default settings of main.py correspond to the MAGPool under hierarchical architecture we proposed in our paper.

So you can simply repeat the experiments via

python main.py

It also contains baseline models and other variants of MAGPool we mentioned in our paper. If you want to try other baselines or variants, please change the value of --model_type into the corresponding ones.

The default dataset is DD, you can change it to other datasets by fill different values to this field.

If you need to change other configurations, please check L216-L260 in main.py and make changes.