For the second time in a week, a long-standing conjecture has been disproved by artificial intelligence, highlighting the ...
Bondy, J.A. and Murty, U.S.R. (1976) Graph Theory with Applications. Macmillan, London and Elsevier.
ABSTRACT: For a simple undirected graph G, let A( G ) be the (0, 1) adjacency matrix of G. The Seidel matrix of G, is defined as S( G )=J−I−2A( G ) , where J is the all-one matrix and I is the ...
All of us solve a “shortest path” problem many times a day. Unintentionally of course. We solve it on our way work or when we browse the Internet or when we arrange our things on a desk. Sounds a bit… ...
Graph neural networks (GNNs) have been applied with great success across science and engineering, but we do not understand why they work so well. Motivated by experimental evidence of a rich phase ...
You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters ...
Hyperscanning is a promising tool for investigating the neurobiological underpinning of social interactions and affective bonds. Recently, graph theory measures, such as modularity, have been proposed ...
Connected networks are a fundamental structure of neurobiology. Understanding these networks will help us elucidate the neural mechanisms of computation. Mathematically speaking these networks are ...
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