42 datasets found

COX2 is a molecular dataset where every graph is classified into one of two classes.

ogbg-molhiv dataset is a graph classification dataset containing 41k molecules.

Open Graph Benchmark (OGB) dataset contains many large-scale benchmark datasets.

Benchmarking graph neural networks.

Graph-ModelNet40, Graph-ModelNet10, Graph-ShapeNet Part are graph datasets constructed for graph classification task.

A synthetic dataset generated for benchmarking GRAPHSHAP, consisting of graphs with controlled motifs injection.

The dataset is used for testing the proposed TopNets architecture on graph classification tasks.

The dataset used in the paper is the reddit-5k and reddit-12k datasets, which consist of social network graphs with 5 and 11 classes, respectively.

MUTAG, NCI1, PTC, PROTEINS, IMDB-BINARY and IMDB-MULTI datasets are graph classification datasets.

The REDDIT-BINARY dataset contains 2,000 graphs labeled as question/answer-based or discussion-based community in the content-aggregation website Reddit.

Deep Graph Neural Networks (GNNs) are useful models for graph classification and graph-based regression tasks. In these tasks, graph pooling is a critical ingredient by which...

Graph classification and node classification datasets

Graph classification and node classification datasets

Graph classification and node classification datasets

The TRIANGLES dataset contains ten different graph classes, corresponding to the number of triangles in each graph in the dataset.

The ENZYMES dataset contains 600 proteins from each of the 6 Enzyme Commission top-level enzyme classes (EC classes) and the goal was to correctly predict enzyme class...

CoraFull is an extension of the prevalent dataset Cora from the entire citation network.

The MUTAG, PTC-MR, PROTEIN, ENZYMES, IMDB-B, and IMDB-M datasets are used to evaluate the performance of the proposed GNAE model.

A dataset for learning distributed representations of graphs using discrete substructure patterns and neural language models.

The dataset used in the paper is a synthetic dataset for graph classification tasks.