Tutorials¶

This page lists the runnable scripts in the examples/ folder.

Run examples from the repository root:

make setup

# Optional setup
make setup-tensorboard

make run examples/gcn.py

Example	What it demonstrates	Run
early_stopping.py	Training with a Lightning `EarlyStopping` callback (MLP HLP, AlgebraDataset, negative sampling)	`make run examples/early_stopping.py`
gcn.py	GCN HLP pipeline on `AlgebraDataset` (negative sampling + LPE enricher)	`make run examples/gcn.py`
hgnn.py	HGNN HLP pipeline on `AlgebraDataset` (negative sampling + LPE enricher)	`make run examples/hgnn.py`
hgnnp.py	HGNNP HLP pipeline on `AlgebraDataset` (negative sampling + LPE enricher)	`make run examples/hgnnp.py`
hnhn.py	HNHN HLP pipeline on `AlgebraDataset` (negative sampling + LPE enricher)	`make run examples/hnhn.py`
hypergcn.py	HyperGCN HLP pipeline on `AlgebraDataset` (hyperedge weights + LPE)	`make run examples/hypergcn.py`
nhp.py	NHP HLP pipeline on `AlgebraDataset` (Node2Vec enricher + negative sampling)	`make run examples/nhp.py`
villain.py	VilLain HLP pipeline on `CoraDataset` (negative sampling)	`make run examples/villain.py`
mlp_common_neighbors.py	MLP HLP and Common Neighbors HLP on `AlgebraDataset` (negative sampling + LPE)	`make run examples/mlp_common_neighbors.py`
node2vecgcn.py	Compute Node2Vec embeddings then train Node2Vec+GCN HLP	`make run examples/node2vecgcn.py`
node2vecslp.py	Compute Node2Vec embeddings then train Node2Vec+SLP HLP	`make run examples/node2vecslp.py`
node_enricher.py	Node feature enrichment: Laplacian positional encoding (LPE) + Node2Vec	`make run examples/node_enricher.py`
hyperedge_enricher.py	Hyperedge enrichment: weights (degree) + hyperedge attributes	`make run examples/hyperedge_enricher.py`