Abstract: Traffic flow prediction is fundamental to intelligent transportation systems, requiring accurate modeling of complex spatio-temporal dependencies. Existing methods typically assume ...
Abstract: Graph neural networks (GNNs) have demonstrated significant advantages in handling data from non-Euclidean domains. Given the successful application of neural architecture search (NAS) in ...
AI users and developers can now measure the amount of electricity various AI models consume to complete tasks with an ...
In an increasingly interconnected world, understanding the behavior and structure of complex networks has become essential across disciplines. These ...
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