-
Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities
Graph pooling is an essential component of the architecture for many graph-level tasks, such as graph classification and graph generation. -
ogbg-molhiv
ogbg-molhiv dataset is a graph classification dataset containing 41k molecules. -
Open Graph Benchmark
Open Graph Benchmark (OGB) dataset contains many large-scale benchmark datasets. -
Benchmark: Datasets for Machine Learning on Graphs
Benchmarking graph neural networks. -
Revisiting link prediction: a data perspective
Revisiting link prediction: a data perspective. -
Synthetic dataset for GRAPHSHAP benchmarking
A synthetic dataset generated for benchmarking GRAPHSHAP, consisting of graphs with controlled motifs injection. -
Graph Classification Benchmark
The dataset is used for testing the proposed TopNets architecture on graph classification tasks. -
Synthetic Graph Classification Dataset
The dataset used in the paper is a synthetic dataset for graph classification tasks.
