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The Preisach model has been useful as a null-model for understanding memory formation in periodically driven disordered systems. In amorphous solids for example, the athermal response to shear is due to localized plastic events (soft…

Soft Condensed Matter · Physics 2020-07-16 M. Mert Terzi , Muhittin Mungan

Exchangeable random graphs serve as an important probabilistic framework for the statistical analysis of network data. In this work we develop an alternative parameterization for a large class of exchangeable random graphs, where the nodes…

Statistics Theory · Mathematics 2020-05-01 Jing Lei

There has been an increased interest in applying machine learning techniques on relational structured-data based on an observed graph. Often, this graph is not fully representative of the true relationship amongst nodes. In these settings,…

Machine Learning · Statistics 2022-08-05 Florence Regol , Soumyasundar Pal , Jianing Sun , Yingxue Zhang , Yanhui Geng , Mark Coates

Interaction graphs, such as those recording emails between individuals or transactions between institutions, tend to be sparse yet structured, and often grow in an unbounded manner. Such behavior can be well-captured by structured,…

Machine Learning · Computer Science 2019-10-15 Elahe Ghalebi , Hamidreza Mahyar , Radu Grosu , Graham W. Taylor , Sinead A. Williamson

This paper is concerned with general spatially explicit versions of three stochastic models for the dynamics of money that have been introduced and studied numerically by statistical physicists: the uniform reshuffling model, the immediate…

Probability · Mathematics 2018-04-18 Nicolas Lanchier , Stephanie Reed

The topology transition problem of transmission networks is becoming increasingly crucial with topological flexibility more widely leveraged to promote high renewable penetration. This paper proposes a novel methodology to address this…

Systems and Control · Electrical Eng. & Systems 2022-09-20 Tong Han , Yue Song , David J. Hill

Many network analysis and graph learning techniques are based on models of random walks which require to infer transition matrices that formalize the underlying stochastic process in an observed graph. For weighted graphs, it is common to…

Methodology · Statistics 2022-10-28 Vincenzo Perri , Luka V. Petrović , Ingo Scholtes

We report the experimental observation of the periodic switching of topological edge states between two dimerized fs-laser written waveguide arrays. Switching occurs due to the overlap of the modal fields of the edge states from topological…

We propose and analyze a graph model to study the connectivity of interdependent networks. Two interdependent networks of arbitrary topologies are modeled as two graphs, where every node in one graph is supported by supply nodes in the…

Discrete Mathematics · Computer Science 2018-09-10 Jianan Zhang , Eytan Modiano

The paper examines the learning mechanism of adaptive agents over weakly-connected graphs and reveals an interesting behavior on how information flows through such topologies. The results clarify how asymmetries in the exchange of data can…

Multiagent Systems · Computer Science 2015-12-08 Bicheng Ying , Ali H. Sayed

In a money exchange process involving a seller and a buyer, we develop a straightforward model encompassing conservative, non-conservative, and systems with or without debt. Our model integrates the Fermi function to capture the behavior of…

Dynamical Systems · Mathematics 2024-09-04 Hsin-Lun Li

Random intersection graphs have received much interest and been used in diverse applications. They are naturally induced in modeling secure sensor networks under random key predistribution schemes, as well as in modeling the topologies of…

Discrete Mathematics · Computer Science 2015-04-14 Jun Zhao , Osman Yağan , Virgil Gligor

We study an ideal-gas-like model where the particles exchange energy stochastically, through energy conserving scattering processes, which take place if and only if at least one of the two particles has energy below a certain energy…

Statistical Mechanics · Physics 2015-05-27 Asim Ghosh , Urna Basu , Anirban Chakraborti , Bikas K. Chakrabarti

Many-body dynamical models in which Boltzmann statistics can be derived directly from the underlying dynamical laws without invoking the fundamental postulates of statistical mechanics are scarce. Interestingly, one such model is found in…

Statistical Mechanics · Physics 2023-11-06 Maggie Miao , Kristian Blom , Dmitrii E. Makarov

Non-fungible tokens (NFTs) as a decentralized proof of ownership represent one of the main reasons why Ethereum is a disruptive technology. This paper presents the first systematic study of the interactions occurring in a number of NFT…

Social and Information Networks · Computer Science 2021-10-26 S. Casale-Brunet , P. Ribeca , P. Doyle , M. Mattavelli

Stochastic reaction networks are mathematical models frequently used in, but not limited to, biochemistry. These models are continuous-time Markov chains whose transition rates depend on certain parameters called rate constants, which…

Probability · Mathematics 2025-08-14 Daniele Cappelletti , Aidan Howells , Chuang Xu

Contagions such as the spread of popular news stories, or infectious diseases, propagate in cascades over dynamic networks with unobservable topologies. However, "social signals" such as product purchase time, or blog entry timestamps are…

Machine Learning · Statistics 2016-12-21 Brian Baingana , Georgios B. Giannakis

We investigate a model of transportation networks with nonlinear elements which may represent local shortage of resources. Frustrations arise from competition for resources. When the initial resources are uniform, different regimes with…

Disordered Systems and Neural Networks · Physics 2009-08-06 C. H. Yeung , K. Y. Michael Wong

Controllability of complex networks arises in many technological problems involving social, financial, road, communication, and smart grid networks. In many practical situations, the underlying topology might change randomly with time, due…

Systems and Control · Computer Science 2020-01-08 Fernando Gama , Elvin Isufi , Alejandro Ribeiro , Geert Leus

The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are…

Disordered Systems and Neural Networks · Physics 2009-11-13 Kartik Anand , Tobias Galla