9 datasets found

Graphs are essential tools to capture and model complicated relationships among data. In a variety of graph applications, including protein-protein interaction networks, social...

Graph embedding is an effective method to represent graph data in a low dimensional space for graph analytics. Most existing embedding algorithms typically focus on preserving...

This dataset contains graph-structured data and its corresponding features.

Citation networks (Cora, CiteSeer, PubMed) and coauthor network (CS) and co-purchase graph (Photo)

The IMM ATT UMIST, COIL USPS, and PIE datasets are used for node classification tasks.

The Cora and Citeseer datasets are used for training machine learning models to classify documents into different categories.

Graph autoencoders (GAEs) are powerful tools in representation learning for graph embedding. However, the performance of GAEs is very dependent on the quality of the graph...

The Ocean Drifter Complex is a dataset formed by using simplicial embedding to represent real-world ocean drifters. The dataset is used to test the performance of an algorithm...

The Citation Complex is a dataset formed by using simplicial embedding to represent real-world citations. The dataset is used to test the performance of an algorithm on...