Mowshowitz, A. Entropy and the complexity of graphs: I. An index of the relative complexity of a graph.Bulletin of Mathematical Biophysics30, 175–204 (1968). https://doi.org/10.1007/BF02476948 Download citation Issue DateMarch 1968 DOI
Graphs (networks) are used as a strong tool for describing the structure of many biological, social and technological systems. The measurement of their complexity has theoretical and practical importance in many areas such as pattern recognition [28], [40], [41], graph clustering [3], network...
Entropy is a classical measure to quantify the amount of information or complexity of a system. Various entropy-based measures such as functional and spectral entropies have been proposed in brain network analysis. However, they are less widely used than traditional graph theoretic measures such as...
This low-order polynomial complexity enables our subgraph kernels to easily scale up to graphs of reasonably large sizes and thus overcome the size limits arising in state-of-the-art graph kernels. Experimental results on fourteen real world graph datasets are shown to demonstrate the overall ...
Many complex networks erase parts of their geometry as they develop, so that their evolution is difficult to quantify and trace. Here we introduce entropy measures for quantifying the complexity of street orientations and length variations within planar networks and apply them to the street networks...
The whole theory, which was developed based on this theorem, deals mainly with combinatorial objects, permutations, graphs, etc.; it is called combinatorial dynamics. The second direction has its main objective in measuring the complexity of a system, or the degree of "chaos" present in it; ...
Part of the book series:SpringerBriefs in Complexity((BRIEFSCOMPLEXITY)) 911Accesses Abstract In this chapter we describe the core method that will be used throughout the rest of the book, i.e. the construction of aconstrained maximum-entropy ensembleof networks. This procedure requires the defin...
14.APanoramaofHungarianMathematicsintheTwentiethCentury,Vol.1 J.Horváth(Ed.) 15.MoreSets,GraphsandNumbers E.Gyri,G.Katona,L.Lovász(Eds.) 16.Entropy,Search,Complexity I.Csiszár,G.Katona,G.Tardos(Eds.) ManagingEditor: Dezs˝oMiklós ImreCsiszár GyulaO.H.Katona GáborTardos(Eds.) Entropy...
The increasing computational complexity limits the statistical estimation of multi-residue interactions that are conditional on a more fine-grained representation of the local environment10,11. In recent years, deep learning has been widely and successfully applied to protein structure modeling and ...
Deterministic and turn-based stochastic Mean-Payoff games are fundamental classes of games with an unsettled complexity. They belong to the complexity class NP ∩ coNP [1], [2], [3] but they are not known to be polynomial-time solvable. Various algorithms have been developed and analyzed. T...