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Recent genomic and bioinformatic advances have motivated the development of numerous random network models purporting to describe graphs of biological, technological, and sociological origin. The success of a model has been evaluated by how…

Molecular Networks · Quantitative Biology 2007-05-23 Manuel Middendorf , Etay Ziv , Carter Adams , Jen Hom , Robin Koytcheff , Chaya Levovitz , Gregory Woods , Linda Chen , Chris Wiggins

The network structure (or topology) of a dynamical network is often unavailable or uncertain. Hence, we consider the problem of network reconstruction. Network reconstruction aims at inferring the topology of a dynamical network using…

Optimization and Control · Mathematics 2018-09-26 Henk J. van Waarde , Pietro Tesi , M. Kanat Camlibel

Constrained counting is a fundamental problem in artificial intelligence. A promising new algebraic approach to constrained counting makes use of tensor networks, following a reduction from constrained counting to the problem of…

Data Structures and Algorithms · Computer Science 2020-04-29 Jeffrey M. Dudek , Leonardo Dueñas-Osorio , Moshe Y. Vardi

We review the main tools which allow for the statistical characterization of weighted networks. We then present two case studies, the airline connection network and the scientific collaboration network, which are representative of critical…

Statistical Mechanics · Physics 2009-11-10 Marc Barthelemy , Alain Barrat , Romualdo Pastor-Satorras , Alessandro Vespignani

We consider a periodic lattice structure in $d=2$ or $3$ dimensions with unit cell comprising $Z$ thin elastic members emanating from a similarly situated central node. A general theoretical approach provides an algebraic formula for the…

Materials Science · Physics 2014-10-09 Andrew N. Norris

We study the network dismantling problem, which consists in determining a minimal set of vertices whose removal leaves the network broken into connected components of sub-extensive size. For a large class of random graphs, this problem is…

Physics and Society · Physics 2016-11-16 Alfredo Braunstein , Luca Dall'Asta , Guilhem Semerjian , Lenka Zdeborová

While deep learning is successful in a number of applications, it is not yet well understood theoretically. A satisfactory theoretical characterization of deep learning however, is beginning to emerge. It covers the following questions: 1)…

Machine Learning · Computer Science 2019-08-27 Tomaso Poggio , Andrzej Banburski , Qianli Liao

Tensor network contraction is central to problems ranging from many-body physics to computer science. We describe how to approximate tensor network contraction through bond compression on arbitrary graphs. In particular, we introduce a…

Quantum Physics · Physics 2024-01-30 Johnnie Gray , Garnet Kin-Lic Chan

The problem of worst case edge deletion from a network is considered. Suppose that you have a communication network and you can delete a single edge. Which edge deletion causes the largest disruption? More formally, given a graph, which…

Data Structures and Algorithms · Computer Science 2022-02-17 Max Ward , Amitava Datta , Hung X. Nguyen , Jason Eshraghian

There has been considerable recent interest in the properties of networks, such as citation networks and the worldwide web, that grow by the addition of vertices, and a number of simple solvable models of network growth have been studied.…

Statistical Mechanics · Physics 2011-11-09 Cristopher Moore , Gourab Ghoshal , M. E. J. Newman

Topological metrics of graphs provide a natural way to describe the prominent features of various types of networks. Graph metrics describe the structure and interplay of graph edges and have found applications in many scientific fields. In…

Data Structures and Algorithms · Computer Science 2018-06-21 Loukianos Spyrou , Javier Escudero

Continuum elasticity is a powerful tool applicable in a broad range of physical systems and phenomena. Yet, understanding how and on what scales material disorder may lead to the breakdown of continuum elasticity is not fully understood. We…

Soft Condensed Matter · Physics 2023-04-11 Edan Lerner , Eran Bouchbinder

This paper investigates the state estimation problem for a class of complex networks, in which the dynamics of each node is subject to Gaussian noise, system uncertainties and nonlinearities. Based on a regularized least-squares approach,…

Systems and Control · Electrical Eng. & Systems 2021-03-16 Peihu Duan , Qishao Wang , Zhisheng Duan , Guanrong Chen

We provide a framework for modeling social network formation through conditional multinomial logit models from discrete choice and random utility theory, in which each new edge is viewed as a "choice" made by a node to connect to another…

Social and Information Networks · Computer Science 2020-05-22 Jan Overgoor , Austin R. Benson , Johan Ugander

Any mass action network gives rise to a parameterised family of polynomial equations whose positive solutions are the positive equilibria of the network. Here, we consider alternative systems of equations, whose solutions are in smooth,…

Molecular Networks · Quantitative Biology 2026-05-06 Murad Banaji , Elisenda Feliu

We provide an approximation result for the pure traction problem of linearized elasticity in terms of local minimizers of finite elasticity, under the constraint of vanishing average curl for admissible deformation maps. When suitable…

Analysis of PDEs · Mathematics 2022-01-26 Edoardo Mainini , Roberto Ognibene , Danilo Percivale

We introduce and study a class of exchangeable random graph ensembles. They can be used as statistical null models for empirical networks, and as a tool for theoretical investigations. We provide general theorems that carachterize the…

Probability · Mathematics 2020-01-09 F. Bassetti , M. Cosentino Lagomarsino , S. Mandrá

Complex networks are frequently employed to model physical or virtual complex systems. When certain entities exist across multiple systems simultaneously, unveiling their corresponding relationships across the networks becomes crucial. This…

Physics and Society · Physics 2025-04-16 Rui Tang , Ziyun Yong , Shuyu Jiang , Xingshu Chen , Yaofang Liu , Yi-Cheng Zhang , Gui-Quan Sun , Wei Wang

This article presents a theoretical investigation of computation beyond the Turing barrier from emergent behavior in distributed systems. In particular, we present an algorithmic network that is a mathematical model of a networked…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-08 Felipe S. Abrahão , Ítala M. Loffredo D'Ottaviano , Klaus Wehmuth , Francisco Antônio Dória , Artur Ziviani

We study the robustness of complex networks subject to edge removal. Several network models and removing strategies are simulated. Rather than the existence of the giant component, we use total connectedness as the criterion of breakdown.…

Physics and Society · Physics 2009-11-13 Shan He , Sheng Li , Hongru Ma