Add a description, image, and links to the graph-patterns topic page so that developers can more easily learn about it ...

Given a set of node groups in a graph (e.g., gender or race groups), how to succinctly summarize their neighbors, and meanwhile ensure a "fair" representation to mitigate under- or over-representation ...

Although graph theoretical approach can be generally applied to either functional or effective connectivity patterns during rest or task performance, to date, most articles have focused on the resting ...

Graph Neural Networks (GNNs) have demonstrated strong power in mining various graph-structure data. Since real-world graphs are usually on a large scale, training scalable GNNs has become one of the ...

Graph neural networks (GNNs) have achieved tremendous success on multiple graph-based learning tasks by fusing network structure and node features. Modern GNN models are built upon iterative ...

The present work aims to investigate the functional connectivity of brain networks when viewing attractive facial pictures. Despite prior research on facial attractiveness having focused on examining ...

The work introduces a linguistic based model designed for distorted or ambiguous patterns where a graph based approach is used for structure representation. The knowledge about unevenness is usually ...

We investigated developmental changes in neuromotor activity patterns in Drosophila melanogaster larvae by combining calcium imaging with a novel graph-based ...