This repository includes the following example scripts:

• MLP: Full-batch MLP training based on paper features and optional Node2Vec features (--use_node_embedding). For training with Node2Vec features, this script requires node embeddings be saved in embedding.pt. To generate them, please run python node2vec.py [requires torch-geometric>=1.5.0].
• GNN: Full-batch GNN training using either the GCN or GraphSAGE operator (--use_sage) [requires torch-geometric>=1.6.0].

# Run with default config
python gnn.py

# Run with custom config
python gnn.py --hidden_channels=128

The tsv file that maps paper IDs into their titles and abstracts are available here. There are three columns: paperid \t title \t abstract. You can obtain the paper ID for each node at mapping/nodeidx2paperid.csv.gz of the downloaded dataset directory.