GNN Cheatsheet

  • SparseTensor: If checked (✓), supports message passing based on torch_sparse.SparseTensor, e.g., GCNConv(...).forward(x, adj_t). See here for the accompanying tutorial.

  • edge_weight: If checked (✓), supports message passing with one-dimensional edge weight information, e.g., GraphConv(...).forward(x, edge_index, edge_weight).

  • edge_attr: If checked (✓), supports message passing with multi-dimensional edge feature information, e.g., GINEConv(...).forward(x, edge_index, edge_attr).

  • bipartite: If checked (✓), supports message passing in bipartite graphs with potentially different feature dimensionalities for source and destination nodes, e.g., SAGEConv(in_channels=(16, 32), out_channels=64).

  • static: If checked (✓), supports message passing in static graphs, e.g., GCNConv(...).forward(x, edge_index) with x having shape [batch_size, num_nodes, in_channels].

  • lazy: If checked (✓), supports lazy initialization of message passing layers, e.g., SAGEConv(in_channels=-1, out_channels=64).

Graph Neural Network Operators

Name

SparseTensor

edge_weight

edge_attr

bipartite

static

lazy

GCNConv (Paper)

ChebConv (Paper)

SAGEConv (Paper)

GraphConv (Paper)

GatedGraphConv (Paper)

ResGatedGraphConv (Paper)

GATConv (Paper)

GATv2Conv (Paper)

TransformerConv (Paper)

AGNNConv (Paper)

TAGConv (Paper)

GINConv (Paper)

GINEConv (Paper)

ARMAConv (Paper)

SGConv (Paper)

APPNP (Paper)

MFConv (Paper)

SignedConv (Paper)

DNAConv (Paper)

PointNetConv (Paper)

PointConv (Paper)

GMMConv (Paper)

SplineConv (Paper)

NNConv (Paper)

ECConv (Paper)

CGConv (Paper)

EdgeConv (Paper)

PPFConv (Paper)

FeaStConv (Paper)

PointTransformerConv (Paper)

LEConv (Paper)

PNAConv (Paper)

ClusterGCNConv (Paper)

GENConv (Paper)

GCN2Conv (Paper)

PANConv (Paper)

WLConv (Paper)

WLConvContinuous (Paper)

SuperGATConv (Paper)

FAConv (Paper)

EGConv (Paper)

PDNConv (Paper)

GeneralConv (Paper)

LGConv (Paper)

Heterogeneous Graph Neural Network Operators

Name

SparseTensor

edge_weight

edge_attr

bipartite

static

lazy

RGCNConv (Paper)

FastRGCNConv (Paper)

RGATConv (Paper)

FiLMConv (Paper)

HGTConv (Paper)

HEATConv (Paper)

HeteroConv (Paper)

HANConv (Paper)

Hypergraph Neural Network Operators

Name

SparseTensor

edge_weight

edge_attr

bipartite

static

lazy

HypergraphConv (Paper)

Point Cloud Neural Network Operators

Name

bipartite

lazy

GravNetConv (Paper)

DynamicEdgeConv (Paper)

XConv (Paper)