The art of finding patterns or communities plays a central role in the analysis of structured data such as networks. Community detection in graphs has become a field on its own. Real-world networks, ...

Directed graphs are crucial in modeling complex real-world systems, from gene regulatory networks and flow networks to stochastic processes and graph metanetworks. Representing these directed graphs ...

Graph theory is an integral component of algorithm design that underlies sparse matrices, relational databases, and networks. Improving the performance of graph algorithms has direct implications to ...

Advanced Artificial Intelligence Theoretical and Computational Chemistry Laboratory, School of Chemistry, University of Hyderabad, Hyderabad, Telangana 500046, India ...

Trophic coherence and non-normality are both ways of describing the overall directionality of directed graphs or networks. Trophic coherence can be regarded as a measure of how neatly a graph can be ...

In this blog post, I will begin by introducing the concept of cut sparsifier for a given graph \(G\), which has been a powerful tool in the design of graph algorithms. Following that, I will present a ...

Previous research on reasoning frameworks in large language models (LLMs) has explored various approaches to enhance problem-solving capabilities. Chain-of-Thought (CoT) introduced articulated ...

X3D-Edit is an Extensible 3D (X3D) Graphics authoring tool for simple error-free creation, editing, validation and viewing of X3D scenes for interactive Web-based visualization. X3D-Edit runs as a ...

In this article, dynamical robustness of a directed complex network with additive noise is inverstigated. The failure of a node in the network is modeled by injecting noise into the node. Under the ...

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