Hypergraph Neural Networks (HGNNs) have been significantly successful in higher-order tasks. However, recent study have shown that they are also vulnerable to adversarial attacks like Graph Neural ...

Uncover the latest and most impactful research in Graph Theory in Probability. Explore pioneering discoveries, insightful ideas and new methods from leading researchers in the field. Mounting ...

Graphs are everywhere. Whenever a delivery company models a road network, a power grid operator tracks the flow of ...

In the realm of machine learning (ML), a knowledge graph is a graphical representation that captures the connections between different entities. It consists of nodes, which represent entities or ...

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Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...