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This paper deals with identifiability of undirected dynamical networks with single-integrator node dynamics. We assume that the graph structure of such networks is known, and aim to find graph-theoretic conditions under which the state…

Optimization and Control · Mathematics 2018-07-24 Henk J. van Waarde , Pietro Tesi , M. Kanat Camlibel

Can evolving networks be inferred and modeled without directly observing their nodes and edges? In many applications, the edges of a dynamic network might not be observed, but one can observe the dynamics of stochastic cascading processes…

Machine Learning · Computer Science 2019-02-26 Elahe Ghalebi , Baharan Mirzasoleiman , Radu Grosu , Jure Leskovec

The present work aims to exploit the interplay between the algebraic properties of rings and the graph-theoretic structures of their associated graphs. We introduce commutatively closed graphs and investigate properties of commutatively…

Rings and Algebras · Mathematics 2021-05-06 André Leroy , Mona Abdi

Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of…

Many real life networks present an average path length logarithmic with the number of nodes and a degree distribution which follows a power law. Often these networks have also a modular and self-similar structure and, in some cases -…

Statistical Mechanics · Physics 2009-02-26 Alicia Miralles , Lichao Chen , Zhongzhi Zhang , Francesc Comellas

The periodic discrete Toda equation defined over finite fields has been studied. We obtained the finite graph structures constructed by the network of states where edges denote possible time evolutions. We simplify the graphs by introducing…

Exactly Solvable and Integrable Systems · Physics 2019-06-19 Masataka Kanki , Yuki Takahashi , Tetsuji Tokihiro

In previous work I examined an information based complexity measure of networks with weighted links. The measure was compared with that obtained from by randomly shuffling the original network, forming an Erdos-Renyi random network…

Information Theory · Computer Science 2014-11-17 Russell Standish

A new modelling approach for the analysis of weighted networks with ordinal/polytomous dyadic values is introduced. Specifically, it is proposed to model the weighted network connectivity structure using a hierarchical multilayer…

Methodology · Statistics 2019-08-05 Alberto Caimo , Isabella Gollini

Network models with latent geometry have been used successfully in many applications in network science and other disciplines, yet it is usually impossible to tell if a given real network is geometric, meaning if it is a typical element in…

Statistical Mechanics · Physics 2016-05-23 Dmitri Krioukov

We introduce a general class of algorithms and supply a number of general results useful for analysing these algorithms when applied to regular graphs of large girth. As a result, we can transfer a number of results proved for random…

Combinatorics · Mathematics 2017-03-06 Carlos Hoppen , Nicholas Wormald

This paper (parts I and II) provides an expository introduction to monotone and near-monotone dynamical systems associated to biochemical networks, those whose graphs are consistent or near-consistent. Many conclusions can be drawn from…

Molecular Networks · Quantitative Biology 2007-05-23 Eduardo D. Sontag

In this short paper, following the most recent advances in complex network theory, a new approach to number theory with potential applications to other fields is proposed. The model by Garcia-Perez, Serrano and Boguna, introduces an…

Physics and Society · Physics 2014-10-06 Daniele Vilone

A determinant property of the structure of a biological network is the distribution of local connectivity patterns, i.e., network motifs. In this work, a method for creating directed, unweighted networks while promoting a certain…

Social and Information Networks · Computer Science 2016-07-29 Tuomo Mäki-Marttunen

We study the evolution of a random weighted network with complex nonlinear dynamics at each node, whose activity may cease as a result of interactions with other nodes. Starting from a knowledge of the micro-level behaviour at each node, we…

Statistical Mechanics · Physics 2007-05-23 Sitabhra Sinha , Sudeshna Sinha

Understanding and interacting with everyday physical scenes requires rich knowledge about the structure of the world, represented either implicitly in a value or policy function, or explicitly in a transition model. Here we introduce a new…

Time evolution equations for dynamical systems can often be derived from generating functionals. Examples are Newton's equations of motion in classical dynamics which can be generated within the Lagrange or the Hamiltonian formalism. We…

Neurons and Cognition · Quantitative Biology 2014-04-23 Claudius Gros

Random graph models are frequently used as a controllable and versatile data source for experimental campaigns in various research fields. Generating such data-sets at scale is a non-trivial task as it requires design decisions typically…

Data Structures and Algorithms · Computer Science 2020-03-03 Manuel Penschuck , Ulrik Brandes , Michael Hamann , Sebastian Lamm , Ulrich Meyer , Ilya Safro , Peter Sanders , Christian Schulz

We consider here the morphogenesis (pattern formation) problem for some genetic network models. First, we show that any given spatio-temporal pattern can be generated by a genetic network involving a sufficiently large number of genes.…

Dynamical Systems · Mathematics 2007-05-23 S. Genieys , S. Vakulenko

We study transient sequential dynamics of evolving dynamical networks, i.e., those having active nodes and links and activity-dependent topology. We show that such networks can generate sequences of metastable cluster states where each…

Chaotic Dynamics · Physics 2014-12-01 Oleg V. Maslennikov , Vladimir I. Nekorkin

We present a method for the construction of ensembles of random networks that consist of a single connected component with a given degree distribution. This approach extends the construction toolbox of random networks beyond the…

Disordered Systems and Neural Networks · Physics 2019-04-19 Ido Tishby , Ofer Biham , Eytan Katzav , Reimer Kühn