ASTGNN

The Relationship Between Graph Neural Networks (GNN) and Neural Networks

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The Relationship Between Graph Neural Networks (GNN) and Neural Networks

1 Introduction Deep neural networks are composed of neurons organized into layers and interconnected, capturing their architecture through computation graphs, where neurons are represented as nodes and directed edges connect different layers of neurons. The performance of neural networks depends on their architecture, but there is currently a lack of systematic understanding of the relationship … Read more

Dynamic Localization of Spatio-Temporal Graph Neural Networks

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Dynamic Localization of Spatio-Temporal Graph Neural Networks

Spatio-temporal data is the foundation of many intelligent applications, revealing the causal relationships between measurements at a specific location and historical data from the same or other locations. In this context, Adaptive Spatio-Temporal Graph Neural Networks (ASTGNNs) have emerged as a powerful tool for modeling these dependencies, particularly through data-driven approaches rather than predefined spatial … Read more