14 datasets found

The dataset used in the paper is a collection of six low-homophily node classification tasks.

Graphs are essential representations of many real-world data such as social networks. Recent years have witnessed the increasing efforts made to extend the neural network models...

The dataset used in the paper is a collection of real-world benchmark datasets for node classification.

The dataset used in the paper is a citation network, specifically Cora, CiteSeer, PubMed, Coauthor-CS, and Coauthor-Physics.

The Coauthor Physics dataset is a co-authorship graph extracted from the Microsoft Academic Graph, with a focus on Physics research.

OGB-MAG is a large-scale dataset used for node classification and link prediction.

DBLP, IMDB, ACM, and Freebase are four public datasets used for node classification and link prediction.

The paper discusses the use of multi-objective Bayesian optimization for hyperparameter transfer in topic models.

Node classification is the task of predicting the labels of unlabeled nodes in a graph. State-of-the-art methods based on graph neural networks achieve excellent performance...

Graph classification and node classification datasets

Graph classification and node classification datasets

Graph classification and node classification datasets

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...

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