Results 1 to 10 of about 35,950 (265)
Navigability of Random Geometric Graphs in the Universe and Other Spacetimes. [PDF]
Sci Rep, 2017 Random geometric graphs in hyperbolic spaces explain many common structural and dynamical properties of real networks, yet they fail to predict the correct values of the exponents of power-law degree distributions observed in real networks.
Cunningham W, Zuev K, Krioukov D.
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Prediction of protein-protein interactions using point transformer and spherical Convex Hull graphs. [PDF]
Comput Struct Biotechnol JAccurate predictions and large-scale identification of protein-protein interactions (PPIs) are crucial for understanding their inherent biological mechanisms and protein functions in virtually all biological processes. Nowadays, graph-based deep learning
Arteaga D, Poptsova M.
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Universal Geometric Graphs [PDF]
Combinatorics, Probability and Computing, 2020 AbstractWe extend the notion of universal graphs to a geometric setting. A geometric graph is universal for a class $\mathcal H$ of planar graphs if it contains an embedding, that is, a crossing-free drawing, of every graph in $\mathcal H$ . Our main result is that there exists a geometric graph with $n$ vertices and $O\!\left(n \log n\right ...
Fabrizio Frati +2 more
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Physical Review E, 2022 We present a new family of graphs with remarkable properties. They are obtained by connecting the points of a random walk when their distance is smaller than a given scale. Their degree (number of neighbors) does not depend on the graph's size but only on the considered scale. It follows a Gamma distribution and thus presents an exponential decay. Levy
S. Plaszczynski +4 more
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Physical Review E, 2002 We analyse graphs in which each vertex is assigned random coordinates in a geometric space of arbitrary dimensionality and only edges between adjacent points are present. The critical connectivity is found numerically by examining the size of the largest cluster. We derive an analytical expression for the cluster coefficient which shows that the graphs
Dall, J., Christensen, Michael
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Colouring random geometric graphs [PDF]
Discrete Mathematics & Theoretical Computer Science, 2005 A random geometric graph $G_n$ is obtained as follows. We take $X_1, X_2, \ldots, X_n ∈\mathbb{R}^d$ at random (i.i.d. according to some probability distribution ν on $\mathbb{R}^d$). For $i ≠j$ we join $X_i$ and $X_j$ by an edge if $║X_i - X_j ║< r(n)$.
Colin J. H. McDiarmid, Tobias Müller
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Geometric Protean Graphs [PDF]
Internet Mathematics, 2012 We study the link structure of on-line social networks (OSNs), and introduce a new model for such networks which may help infer their hidden underlying reality. In the geo-protean (GEO-P) model for OSNs nodes are identified with points in Euclidean space, and edges are stochastically generated by a mixture of the relative distance of nodes and a ...
Bonato, Anthony +2 more
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On arithmetic–geometric eigenvalues of graphs
Main Group Metal Chemistry, 2022 In this article, we are interested in characterizing graphs with three distinct arithmetic–geometric eigenvalues. We provide the bounds on the arithmetic–geometric energy of graphs. In addition, we carry out a statistical analysis of arithmetic–geometric
Rather Bilal A. +3 more
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NeuroImage, 2021 Diffusion MRI tractography is the only noninvasive method to measure the structural connectome in humans. However, recent validation studies have revealed limitations of modern tractography approaches, which lead to significant mistracking caused in part
Scott Trinkle +4 more
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Generalizing Geometric Graphs [PDF]
Journal of Graph Algorithms and Applications, 2012 Summary: Network visualization is essential for understanding the data obtained from huge real-world networks such as flight-networks, the AS-network or social networks. Although we can compute layouts for these networks reasonably fast, even the most recent display media are not capable of displaying these layouts in an adequate way.
Brunel, E. +4 more
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