Abstract: Random walk centrality is a fundamental metric in graph mining for quantifying node importance and influence, defined as the weighted average of hitting times to a node from all other nodes.

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

If you’ve ever shuffled a deck of playing cards, you’ve most likely created a unique deck. That is, you’re probably the only person who has ever arranged the cards in precisely that order. Although ...

Abstract: Vision Graph Neural Network (ViG) is the first graph neural network model capable of directly processing image data. The community primarily focuses on the model structures to improve ViG's ...

There is a new sorting algorithm a deterministic O(m log2/3 n)-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition ...

If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle the easiest pieces first. But this kind of sorting has a cost.

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The processing of chemical information by computational intelligence methods faces the ...

ABSTRACT: To effectively evaluate a system that performs operations on UML class diagrams, it is essential to cover a large variety of different types of diagrams. The coverage of the diagram space ...