Graph anomaly detection (GAD) has attracted increasing interest due to its critical role in diverse real-world applications. Graph neural networks (GNNs) offer a promising avenue for GAD, leveraging ...

Introduction: Voxel hierarchy on dynamic brain graphs is produced by k-core percolation on functional dynamic amplitude correlation of resting-state fMRI. Methods: Directed graphs and their ...

Brualdi, R.A. and Goldwasser, J.L. (1984) Permanent of the Laplacian Matrix of Trees and Bipartite Graphs. Discrete Mathematics, 48, 1-21.

Welcome to LetsPS! 🎨🖥️ Master Photoshop, Illustrator, and InDesign with step-by-step tutorials designed to help you create stunning artwork! From photo manipulations and text effects to ...

We introduce an anomaly detection approach for EEG channels and segments based on inter-channel correlation analysis. This method utilizes Graph Neural Networks (GNNs) (15, 16) to capture the ...

A correlation matrix is a valuable statistical tool that appraisers can use to assess relationships between different variables, ensuring that they produce thorough, defensible, and reproducible ...

Deep graph clustering, which aims to reveal the underlying graph structure and divide the nodes into different clusters without human annotations, is a fundamental yet challenging task. However, we ...