Graph Convolutional Networks (GCNs) are widely applied for spatial domain identification in spatial transcriptomics (ST), where node representations are learned by aggregating information from ...

Accurate prediction of protein-protein interactions (PPIs) is crucial for understanding cellular functions and advancing the development of drugs. While existing in-silico methods leverage direct ...

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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 ...

1 Department of Computer Engineering, School of Engineering, The University of Jordan, Amman, Jordan. 2 Department of Data Science and Artificial Intelligence, Faculty of Information Technology, ...

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Abstract: Attribute graph clustering is a fundamental and challenging task in graph data mining, requiring the adequate utilization of both node attributes and graph structure. Recently, a series of ...

Abstract: Skeleton-based hand gesture recognition is a challenging task that sparked a lot of attention in recent years, especially with the rise of Graph Neural Networks. In this paper, we propose a ...