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Contact processes describe the transmission of distinct properties of nodes via the links of a network. They provide a simple framework for many phenomena, such as epidemic spreading and opinion formation. Combining contact processes with…

Physics and Society · Physics 2010-11-12 Anne-Ly Do , Thilo Gross

Many of the essential features of the evolution of scientific research are imprinted in the structure of citation networks. Connections in these networks imply information about the transfer of knowledge among papers, or in other words,…

Physics and Society · Physics 2014-05-23 Enys Mones , Péter Pollner , Tamás Vicsek

We describe a coordinate-free notion of conformal nets as a mathematical model of conformal field theory. We define defects between conformal nets and introduce composition of defects, thereby providing a notion of morphism between…

Algebraic Topology · Mathematics 2010-10-12 Arthur Bartels , Christopher L. Douglas , André G. Henriques

Phylogenetic networks are a generalization of phylogenetic trees that are used to represent reticulate evolution. Unrooted phylogenetic networks form a special class of such networks, which naturally generalize unrooted phylogenetic trees.…

Populations and Evolution · Quantitative Biology 2016-01-11 Katharina T. Huber , Vincent Moulton , Taoyang Wu

We introduce a new formalism for representing proofs in propositional logic called "scroll nets". Its fundamental construct is the "scroll", a topological notation for implication proposed by C. S. Peirce at the end of the 19th century as…

Logic in Computer Science · Computer Science 2025-07-29 Pablo Donato

Networks are a fundamental model of complex systems throughout the sciences, and network datasets are typically analyzed through lower-order connectivity patterns described at the level of individual nodes and edges. However, higher-order…

Social and Information Networks · Computer Science 2018-02-21 Austin R. Benson

Directed acyclic graphs are a fundamental class of networks that includes citation networks, food webs, and family trees, among others. Here we define a random graph model for directed acyclic graphs and give solutions for a number of the…

Physics and Society · Physics 2009-03-23 Brian Karrer , M. E. J. Newman

One explanation for the impressive recent boom in network theory might be that it provides a promising tool for an understanding of complex systems. Network theory is mainly focusing on discrete large-scale topological structures rather…

Statistical Mechanics · Physics 2015-06-25 Stefan Thurner

All types of networks arise as intricate combinations of dyadic building blocks formed by pairs of vertices. In directed networks, the dyadic patterns are entirely determined by reciprocity, i.e. the tendency to form, or to avoid, mutual…

Data Analysis, Statistics and Probability · Physics 2014-01-14 Tiziano Squartini , Francesco Picciolo , Franco Ruzzenenti , Diego Garlaschelli

Petri nets are a formalism for modelling and reasoning about the behaviour of distributed systems. Recently, a reversible approach to Petri nets, Reversing Petri Nets (RPN), has been proposed, allowing transitions to be reversed…

Logic in Computer Science · Computer Science 2019-05-30 Anna Philippou , Kyriaki Psara , Harun Siljak

A thesaurus is one, out of many, possible representations of term (or word) connectivity. The terms of a thesaurus are seen as the nodes and their relationship as the links of a directed graph. The directionality of the links retains all…

We propose an explanatory and computational theory of transformative discoveries in science. The theory is derived from a recurring theme found in a diverse range of scientific change, scientific discovery, and knowledge diffusion theories…

General Literature · Computer Science 2010-02-09 Chaomei Chen , Yue Chen , Mark Horowitz , Haiyan Hou , Zeyuan Liu , Don Pellegrino

We give a tutorial for the study of dynamical systems on networks. We focus especially on "simple" situations that are tractable analytically, because they can be very insightful and provide useful springboards for the study of more…

Adaptation and Self-Organizing Systems · Physics 2015-05-05 Mason A. Porter , James P. Gleeson

Many "good" topologies for interconnection networks are based on line digraphs of regular digraphs. These digraphs support unitary matrices. We propose the property "being the digraph of a unitary matrix" as additional criterion for the…

Discrete Mathematics · Computer Science 2007-05-23 Simone Severini

Transport networks are crucial to the functioning of natural and technological systems. Nature features transport networks that are adaptive over a vast range of parameters, thus providing an impressive level of robustness in supply.…

Adaptation and Self-Organizing Systems · Physics 2017-11-28 Erik Andreas Martens , Konstantin Klemm

Neural networks have become an increasingly popular tool for solving many real-world problems. They are a general framework for differentiable optimization which includes many other machine learning approaches as special cases. In this…

Machine Learning · Computer Science 2019-07-22 Bruno Gavranović

Network structure strongly constrains the range of dynamic behaviors available to a complex system. These system dynamics can be classified based on their response to perturbations over time into two distinct regimes, ordered or chaotic,…

Disordered Systems and Neural Networks · Physics 2009-11-13 Matti Nykter , Nathan D. Price , Antti Larjo , Tommi Aho , Stuart A. Kauffman , Olli Yli-Harja , Ilya Shmulevich

This article reviews and evaluates models of network evolution based on the notion of structural diversity. We show that diversity is an underlying theme of three principles of network evolution: the preferential attachment model,…

Social and Information Networks · Computer Science 2020-09-22 Jérôme Kunegis

The large and still increasing popularity of deep learning clashes with a major limit of neural network architectures, that consists in their lack of capability in providing human-understandable motivations of their decisions. In situations…

Machine Learning · Computer Science 2023-05-22 Gabriele Ciravegna , Pietro Barbiero , Francesco Giannini , Marco Gori , Pietro Lió , Marco Maggini , Stefano Melacci

Motivated by the idea that criticality and universality of phase transitions might play a crucial role in achieving and sustaining learning and intelligent behaviour in biological and artificial networks, we analyse a theoretical and a…

Artificial Intelligence · Computer Science 2017-06-01 Dan Oprisa , Peter Toth