22 datasets found

The dataset used in the paper is Amazon clothing, Amazon-Electronics, and DBLP.

The dataset used in this paper is a collection of real-world graph datasets from various domains, including biological networks, social networks, and collaboration networks.

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

A dataset for learning combinatorial optimization algorithms over graphs.

Real-world data generation often involves certain geometries (e.g., graphs) that induce instance-level interdependence.

Real-world data generation often involves certain geometries (e.g., graphs) that induce instance-level interdependence.

The dataset used in the paper consists of 10 different ER graphs with varying densities.

The dataset used in the paper is citation networks, including Cora, Citeseer, and Pubmed.

The dataset used in the paper is a graph, where each node represents a node in the graph and each edge represents a relation between nodes.

The dataset used in the paper is a graph, where each node represents a node in the graph and each edge represents a relation between nodes.

The dataset used in the paper is a collection of explicit interactions gathered from various sources, including music websites, movie ratings, book clubs, social networks, and...

MOOC dataset is a collection of students' answer records on various knowledge concepts in computer science.

KarateClub is a small and undirected graph consisting of 34 nodes and 156 edges.

Generative models of graphs are well-known, but many existing models are limited in scalability and expressivity. We present a novel sequential graphical variational autoencoder...

The dataset used in the paper is a multi-graph problem, where each graph represents a different network. The dataset is used to evaluate the performance of the RECS algorithm on...

The BlogCatalog dataset is a blog directory that manages bloggers and their blogs. Each unit is a blogger and the features are bag-of-words representations of keywords in...

Graph Neural Networks (GNNs) have emerged as powerful tools for learning graph-structured data in various domains.

Graph Edit Distance as a quadratic assignment problem.

Graphs are frequently used in various fields of computer science, since they constitute a universal modeling tool which allows the description of structured data.

The dataset used in the paper is a citation network, specifically the Cora, Citeseer, and PubMed datasets.