The Reddit dataset from the “GraphSAINT: Graph Sampling Based Inductive Learning Method” paper, containing Reddit posts belonging to different communities. The Reddit dataset from the “Inductive Representation Learning on Large Graphs” paper, containing Reddit posts belonging to different communities.
The protein-protein interaction networks from the “Predicting Multicellular Function through Multi-layer Tissue Networks” paper, containing positional gene sets, motif gene sets and immunological signatures as features (50 in total) and gene ontology sets as labels (121 in total). The Amazon Computers and Amazon Photo networks from the “Pitfalls of Graph Neural Network Evaluation” paper. The Coauthor CS and Coauthor Physics networks from the “Pitfalls of Graph Neural Network Evaluation” paper.
The full citation network datasets from the “Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking” paper.Īlias for torch_ with name="cora". The NELL dataset, a knowledge graph from the “Toward an Architecture for Never-Ending Language Learning” paper. The citation network datasets “Cora”, “CiteSeer” and “PubMed” from the “Revisiting Semi-Supervised Learning with Graph Embeddings” paper.Ī fake dataset that returns randomly generated Data objects.Ī fake dataset that returns randomly generated HeteroData objects. “IMDB-BINARY”, “REDDIT-BINARY” or “PROTEINS”, collected from the TU Dortmund University.Ī variety of artificially and semi-artificially generated graph datasets from the “Benchmarking Graph Neural Networks” paper. Zachary’s karate club network from the “An Information Flow Model for Conflict and Fission in Small Groups” paper, containing 34 nodes, connected by 156 (undirected and unweighted) edges.Ī variety of graph kernel benchmark datasets. Heterogeneous Graph Neural Network Operators.