82 datasets found

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 an electrostatic problem with a three-dimensional, irregular geometry.

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

The CORD-19 dataset contains academic journal articles relating to a variety of coronaviruses and related viral infections, not only COVID-19, sourced from PubMed Central (PMC),...

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.

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

The dataset used in this paper is the Polblogs dataset, which contains 1,222 blogs.

The dataset is used to test the performance of Tangent Bundle Neural Networks on three tasks: denoising of a tangent vector field on the torus, reconstruction from partial...