49 datasets found

CORA, Citeseer, Pubmed, OGB arXiv

The dataset used in the paper is a collection of nine graphs with different degrees of homophily.

The dataset used in the paper is a comprehensive survey on graph neural networks.

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...

Graph representation learning typically aims to learn an informative embedding for each graph node based on the graph topology (link) information.

Graph Neural Networks (GNNs) have become a popular approach for various applications, ranging from social network analysis to modeling chemical properties of molecules.

The Temporal Occupancy Flow Graph (TOFG) is a unified environment representation that unifies the map information and vehicle trajectories in a homogeneous graph.

The authors used the Moleculenet dataset for their experiments.

The authors used the TEXAS dataset for their experiments.

PCQM4M is a quantum chemistry dataset originally curated under the PubChemQC project.

Open Graph Benchmark: Datasets for machine learning on graphs.

The dataset used in the paper is a graph dataset, where each node represents a person and each edge represents a connection between two people. The dataset is used to evaluate...

The dataset used in the paper is a graph dataset, where each node represents a person and each edge represents a connection between two people. The dataset is used to evaluate...

The IMDB-Binary dataset is a graph neural network dataset.

The Proteins dataset is a graph neural network dataset.

Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces

The dataset used in the paper is a link prediction benchmark dataset (Cora, PubMed, Disease, Airport) with a Gromov θ-hyperbolicity value.

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

Bipartite graphs with capacities and weights, used for training and evaluation of neural bipartite matching.