ABSTRACT: Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex ...
Abstract: Graph Neural Networks (GNNs) have been gaining more attention due to their excellent performance in modeling various graph-structured data. However, most of the current GNNs only consider ...
Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
Abstract: A dynamic directed graph (DDG) can describe complex dynamic interactions among massive entities, for example, traffic transmissions in a metropolitan area network (MAN), in a natural way.
Graph neural networks in Alzheimer's disease diagnosis: a review of unimodal and multimodal advances
Alzheimer's Disease (AD), a leading neurodegenerative disorder, presents significant global health challenges. Advances in graph neural networks (GNNs) offer promising tools for analyzing multimodal ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator.
A revision equals a git commit. In the graph a revision is a node in the graph. This is visually represented with a filled circle. Each commit/revision is rendered on a separate a row in the graph.
School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China Advanced Sensor Research Institution, Northeast Electric Power University, Jilin 132012, China School of ...
1 College of Computer Science and Engineering, Changsha University, Changsha, Hunan, China 2 Department of Information and Computing Science, College of Mathematics, Changsha University, Changsha, ...
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