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Community detection, which focuses on clustering nodes or detecting communities in (mostly) a single network, is a problem of considerable practical interest and has received a great deal of attention in the research community. While being…

Machine Learning · Statistics 2017-11-07 Soumendu Sundar Mukherjee , Purnamrita Sarkar , Lizhen Lin

We study fully synchronized states in scale-free networks of chaotic logistic maps as a function of both dynamical and topological parameters. Three different network topologies are considered: (i) random scale-free topology, (ii)…

Disordered Systems and Neural Networks · Physics 2009-11-10 Pedro G. Lind , Jason A. C. Gallas , Hans J. Herrmann

Motivated by social balance theory, we develop a theory of link classification in signed networks using the correlation clustering index as measure of label regularity. We derive learning bounds in terms of correlation clustering within…

Machine Learning · Computer Science 2013-03-01 Nicolo Cesa-Bianchi , Claudio Gentile , Fabio Vitale , Giovanni Zappella

In this paper we generalize the concept of random networks to describe networks with non trivial features by a statistical mechanics approach. This framework is able to describe ensembles of undirected, directed as well as weighted…

Disordered Systems and Neural Networks · Physics 2009-11-13 Ginestra Bianconi

Natural and man-made transport webs are frequently dominated by dense sets of nested cycles. The architecture of these networks, as defined by the topology and edge weights, determines how efficiently the networks perform their function.…

Quantitative Methods · Quantitative Biology 2016-07-27 Carl D. Modes , Marcelo O. Magnasco , Eleni Katifori

Computer networks are the foundation of modern digital infrastructure, facilitating global communication and data exchange. As demand for reliable high-bandwidth connectivity grows, advanced network modeling techniques become increasingly…

We consider the multi-broadcast problem in arbitrary connected radio networks consisting of $n$ nodes. There are $k$ designated source nodes for some fixed $k \in \{1,\ldots,n\}$, and each source node has a distinct piece of information…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-04-20 Colin Krisko , Avery Miller

A method for embedding graphs in Euclidean space is suggested. The method connects nodes to their geographically closest neighbors and economizes on the total physical length of links. The topological and geometrical properties of…

Condensed Matter · Physics 2007-05-23 Daniel ben-Avraham , Alejandro F. Rozenfeld , Reuven Cohen , Shlomo Havlin

We introduce new geometric objects called spectral networks. Spectral networks are networks of trajectories on Riemann surfaces obeying certain local rules. Spectral networks arise naturally in four-dimensional N=2 theories coupled to…

High Energy Physics - Theory · Physics 2015-06-04 Davide Gaiotto , Gregory W. Moore , Andrew Neitzke

We study the structure of loops in networks using the notion of modulus of loop families. We introduce a new measure of network clustering by quantifying the richness of families of (simple) loops. Modulus tries to minimize the expected…

Social and Information Networks · Computer Science 2017-01-25 Heman Shakeri , Pietro Poggi-Corradini , Nathan Albin , Caterina Scoglio

In phylogenetics, it is important for the phylogenetic network model parameters to be identifiable so that the evolutionary histories of a group of species can be consistently inferred. However, as the complexity of the phylogenetic network…

Populations and Evolution · Quantitative Biology 2021-04-27 Muhammad Ardiyansyah

In this paper we describe an approach to construct large extendable collections of vectors in predefined spaces of given dimensions. These collections are useful for neural network latent space configuration and training. For classification…

Algebraic Geometry · Mathematics 2025-12-05 Igor V. Netay

The $\mathsf{HYBRID}$ model was introduced as a means for theoretical study of distributed networks that use various communication modes. Conceptually, it is a synchronous message passing model with a local communication mode, where in each…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-15 Fabian Kuhn , Philipp Schneider

This paper mainly investigates why small-world networks are navigable and how to navigate small-world networks. We find that the navigability can naturally emerge from self-organization in the absence of prior knowledge about underlying…

Social and Information Networks · Computer Science 2015-05-20 Zhao Zhuo , Shi-Min Cai , Zhong-Qian Fu , Wen-Xu Wang

The new concept of multilevel network is introduced in order to embody some topological properties of complex systems with structures in the mesoscale which are not completely captured by the classical models. This new model, which…

Recently, so-called treebased phylogenetic networks have gained considerable interest in the literature, where a treebased network is a network that can be constructed from a phylogenetic tree, called the base tree, by adding additional…

Populations and Evolution · Quantitative Biology 2019-11-28 Mareike Fischer , Michelle Galla , Lina Herbst , Yangjing Long , Kristina Wicke

After generalizing the concept of clusters to incorporate clusters that are linked to other clusters through some relatively narrow bridges, an approach for detecting patches of separation between these clusters is developed based on an…

Computer Vision and Pattern Recognition · Computer Science 2020-01-10 Luciano da F. Costa

Boundary labeling is a well-known method for displaying short textual labels for a set of point features in a figure alongside the boundary of that figure. Labels and their corresponding points are connected via crossing-free leaders. We…

Computational Geometry · Computer Science 2024-09-06 Annika Bonerath , Martin Nöllenburg , Soeren Terziadis , Markus Wallinger , Jules Wulms

Many real networks share three generic properties: they are scale-free, display a small-world effect, and show a power-law strength-degree correlation. In this paper, we propose a type of deterministically growing networks called Sierpinski…

Physics and Society · Physics 2007-07-16 Zhongzhi Zhang , Shuigeng Zhou , Lujun Fang , Jihong Guan , Yichao Zhang

Recently there have been a tremendous interest in models of networks with a power-law distribution of degree -- so called "scale-free networks." It has been observed that such networks, normally, have extremely short path-lengths, scaling…

Disordered Systems and Neural Networks · Physics 2007-05-23 Petter Holme
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