Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring. These methods ...

Graphs naturally generalize unstructured vectorial data and structured data such as time series, images or bags of entities. The goal of this course is to provide an overview of the fundamental ...

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Knowledge graphs are more than just a data structure; they are a fundamental tool that allows AI to mirror the complexity of the real world.

József Balogh, Robert Morris, Wojciech Samotij, Lutz Warnke, The typical structure of sparse Kr+1-free graphs, Transactions of the American Mathematical Society, Vol. 368, No. 9 (September 2016), pp.

Knowledge graphs , which are essential for internet searches and machine learning, use a graph structure to link various pieces of knowledge and link data to perform knowledge exploration and ...

Graphs are among the most widely-used data structures in machine learning. Their power comes from the flexibility of capturing relations (edges) of collections of entities (nodes) which arise in a ...