IEEE

Multigranularity Deep Graph Convolutional Neural Network Node Clustering Leveraging Spatial Information

Abstract: In the era of information explosion, clustering analysis of graph-structured data and empty graph-structured data is of great significance for extracting the intrinsic value of data. From ...
Forbes

Security Graphs Explained: An Innovative Approach To Network Security

Imagine standing atop a mountain, gazing at the vast landscape below, trying to make sense of the world around you. For centuries, explorers relied on such vantage points to map their surroundings.
Scientific Research Publishing

Ibrahim, A.A., Mohammed, T.A. and Dara, O.N. (2024) Predicting Big Data Drug Interactions and Associated Side Effects by Using Artificial Neural Networks (ANN) over Traditional ...

ABSTRACT: Managing psychiatric disorders, including depression, anxiety, and bipolar disorder, during pregnancy presents significant clinical challenges due to uncertainties surrounding medication ...
Quanta Magazine

New Proof Settles Decades-Old Bet About Connected Networks

According to mathematical legend, Peter Sarnak and Noga Alon made a bet about optimal graphs in the late 1980s. They’ve now both been proved wrong. It started with a bet. In the late 1980s, at a ...
IEEE

Augmented Graph Convolutional Network for Enhancing Label Reachability

Abstract: Graph Convolutional Networks (GCNs) have emerged as a leading approach for semi-supervised node classification. However, due to the uneven distribution of labeled nodes in graphs, only a ...