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We derive an exact representation of the topological effect on the dynamics of sequence processing neural networks within signal-to-noise analysis. A new network structure parameter, loopiness coefficient, is introduced to quantitatively…

Disordered Systems and Neural Networks · Physics 2008-05-11 Pan Zhang , Yong Chen

We consider relations between the size, treewidth, and local crossing number (maximum number of crossings per edge) of graphs embedded on topological surfaces. We show that an $n$-vertex graph embedded on a surface of genus $g$ with at most…

Combinatorics · Mathematics 2017-07-18 Vida Dujmović , David Eppstein , David R. Wood

We consider so-called simple families of labelled trees, which contain, e.g., ordered, unordered, binary and cyclic labelled trees as special instances, and study the global and local behaviour of the number of inversions. In particular we…

Combinatorics · Mathematics 2011-01-26 Alois Panholzer , Georg Seitz

We present scaling laws that dictate both local and global connectivity properties of bounded wireless networks. These laws are defined with respect to the key system parameters of per-node transmit power and the number of antennas…

Networking and Internet Architecture · Computer Science 2017-06-15 Justin P. Coon , Orestis Georgiou , Carl P. Dettmann

Measuring and optimizing the influence of nodes in big-data online social networks are important for many practical applications, such as the viral marketing and the adoption of new products. As the viral spreading on social network is a…

Physics and Society · Physics 2018-07-31 Yanqing Hu , Shenggong Ji , Yuliang Jin , Ling Feng , H. Eugene Stanley , Shlomo Havlin

We investigate the behavior of the empirical neighbourhood distribution of marked graphs in the framework of local weak convergence. We establish a large deviation principle for such families of empirical measures. The proof builds on…

Probability · Mathematics 2024-01-02 Rangel Baldasso , Alan Pereira , Guilherme Reis

Learning embeddings from large-scale networks is an open challenge. Despite the overwhelming number of existing methods, is is unclear how to exploit network structure in a way that generalizes easily to unseen nodes, edges or graphs. In…

Machine Learning · Computer Science 2020-09-29 Nurudin Alvarez-Gonzalez , Andreas Kaltenbrunner , Vicenç Gómez

Most real-world networks are embedded in latent geometries. If a node in a network is found in the vicinity of another node in the latent geometry, the two nodes have a disproportionately high probability of being connected by a link. The…

Physics and Society · Physics 2024-06-19 Bukyoung Jhun

One major open problem in network coding is to characterize the capacity region of a general multi-source multi-demand network. There are some existing computational tools for bounding the capacity of general networks, but their…

Information Theory · Computer Science 2015-03-17 Michelle Effros , Tracey Ho , Shirin Jalali

In this paper, we derive theoretical bounds for the long-term influence of a node in an Independent Cascade Model (ICM). We relate these bounds to the spectral radius of a particular matrix and show that the behavior is sub-critical when…

Probability · Mathematics 2014-07-18 Remi Lemonnier , Kevin Scaman , Nicolas Vayatis

The aim of this paper is to propose a novel framework to infer the sheaf Laplacian, including the topology of a graph and the restriction maps, from a set of data observed over the nodes of a graph. The proposed method is based on sheaf…

Signal Processing · Electrical Eng. & Systems 2025-02-03 Leonardo Di Nino , Sergio Barbarossa , Paolo Di Lorenzo

In this article we study the treewidth of the \emph{display graph}, an auxiliary graph structure obtained from the fusion of phylogenetic (i.e., evolutionary) trees at their leaves. Earlier work has shown that the treewidth of the display…

Discrete Mathematics · Computer Science 2017-04-03 Steven Kelk , Georgios Stamoulis , Taoyang Wu

Common definitions of the "standard" LOCAL model tend to be sloppy and even self-contradictory on one point: do the nodes update their state using an arbitrary function or a computable function? So far, this distinction has been safe to…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-26 Antonio Cruciani , Avinandan Das , Massimo Equi , Henrik Lievonen , Diep Luong-Le , Augusto Modanese , Jukka Suomela

Two node variables determine the evolution of cascades in random networks: a node's degree and threshold. Correlations between both fundamentally change the robustness of a network, yet, they are disregarded in standard analytic methods as…

Adaptation and Self-Organizing Systems · Physics 2018-08-15 Rebekka Burkholz , Frank Schweitzer

The landscape of the distributed time complexity is nowadays well-understood for subpolynomial complexities. When we look at deterministic algorithms in the LOCAL model and locally checkable problems (LCLs) in bounded-degree graphs, the…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-26 Alkida Balliu , Sebastian Brandt , Dennis Olivetti , Jukka Suomela

This article studies the limit of binary search trees drawn from Mallows permutations under various topologies. The main result, pertaining to the standard local topology for graphs, requires the introduction of a generalization of binary…

Probability · Mathematics 2023-12-22 Benoît Corsini

Phylogenetic trees and networks are leaf-labelled graphs used to model evolution. Display graphs are created by identifying common leaf labels in two or more phylogenetic trees or networks. The treewidth of such graphs is bounded as a…

Data Structures and Algorithms · Computer Science 2018-09-05 Remie Janssen , Mark Jones , Steven Kelk , Georgios Stamoulis , Taoyang Wu

We determine if the width of a graph class ${\cal G}$ changes from unbounded to bounded if we consider only those graphs from ${\cal G}$ whose diameter is bounded. As parameters we consider treedepth, pathwidth, treewidth and clique-width,…

Discrete Mathematics · Computer Science 2025-05-27 Konrad K. Dabrowski , Tala Eagling-Vose , Noleen Köhler , Sebastian Ordyniak , Daniël Paulusma

We propose a local strategy for constructing scale-free networks of arbitrary degree distributions, based on the redirection method of Krapivsky and Redner [Phys. Rev. E 63, 066123 (2001)]. Our method includes a set of external parameters…

Disordered Systems and Neural Networks · Physics 2009-11-10 Hernan Rozenfeld , Daniel ben-Avraham

From social interactions to the human brain, higher-order networks are key to describe the underlying network geometry and topology of many complex systems. While it is well known that network structure strongly affects its function, the…

Statistical Mechanics · Physics 2022-01-11 Ana P Millán , Reza Ghorbanchian , Nicolò Defenu , Federico Battiston , Ginestra Bianconi
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