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Related papers: Weighted Growing Simplicial Complexes

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This work explores hypernetworks: an approach of using a one network, also known as a hypernetwork, to generate the weights for another network. Hypernetworks provide an abstraction that is similar to what is found in nature: the…

Machine Learning · Computer Science 2016-12-02 David Ha , Andrew Dai , Quoc V. Le

We review a collection of models of random simplicial complexes together with some of the most exciting phenomena related to them. We do not attempt to cover all existing models, but try to focus on those for which many important results…

Probability · Mathematics 2022-05-04 Omer Bobrowski , Dmitri Krioukov

Simplicial complexes are a versatile and convenient paradigm on which to build all the tools and techniques of the logic of knowledge, on the assumption that initial epistemic models can be described in a distributed fashion. Thus, we can…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-06 Hans van Ditmarsch , Eric Goubault , Jeremy Ledent , Sergio Rajsbaum

Combinatorial topology is used in distributed computing to model concurrency and asynchrony. The basic structure in combinatorial topology is the simplicial complex, a collection of subsets called simplices of a set of vertices, closed…

Logic in Computer Science · Computer Science 2024-02-14 Rojo Randrianomentsoa , Hans van Ditmarsch , Roman Kuznets

Topological signals, i.e., dynamical variables defined on nodes, links, triangles, etc. of higher-order networks, are attracting increasing attention. However the investigation of their collective phenomena is only at its infancy. Here we…

Statistical Mechanics · Physics 2023-05-17 Timoteo Carletti , Lorenzo Giambagli , Ginestra Bianconi

We explore the interplay between the protein-protein interactions network and the expression of the interacting proteins. It is shown that interacting proteins are expressed in significantly more similar cellular concentrations. This is…

Molecular Networks · Quantitative Biology 2007-05-23 Shai Carmi , Erez Y. Levanon , Shlomo Havlin , Eli Eisenberg

Complex networks representing social interactions, brain activities, molecular structures have been studied widely to be able to understand and predict their characteristics as graphs. Models and algorithms for these networks are used in…

Social and Information Networks · Computer Science 2022-10-24 Murat Çelik , Ali Baran Taşdemir , Lale Özkahya

Weighted networks capture the structure of complex systems where interaction strength is meaningful. This information is essential to a large number of processes, such as threshold dynamics, where link weights reflect the amount of…

Physics and Society · Physics 2021-04-28 Samuel Unicomb , Gerardo Iñiguez , Márton Karsai

Contrary to many recent models of growing networks, we present a model with fixed number of nodes and links, where it is introduced a dynamics favoring the formation of links between nodes with degree of connectivity as different as…

Statistical Mechanics · Physics 2007-05-23 M. Baiesi , S. S. Manna

Understanding spreading dynamics will benefit society as a whole in better preventing and controlling diseases, as well as facilitating the socially responsible information while depressing destructive rumors. In network-based spreading…

Physics and Society · Physics 2015-01-16 Ai-Xiang Cui , Zimo Yang , Tao Zhou

Building on previous work, this paper extends the modeling of political structures from simplicial complexes to hypergraphs. This allows the analysis of more complex political dynamics where agents who are willing to form coalitions contain…

Physics and Society · Physics 2024-04-24 Ismar Volic , Zixu Wang

Graphs can model networked data by representing them as nodes and their pairwise relationships as edges. Recently, signal processing and neural networks have been extended to process and learn from data on graphs, with achievements in tasks…

Machine Learning · Computer Science 2021-10-07 Maosheng Yang , Elvin Isufi , Geert Leus

We describe the dynamics of a simple adaptive network. The network architecture evolves to a number of disconnected components on which the dynamics is characterized by the possibility of differently synchronized nodes within the same…

Adaptation and Self-Organizing Systems · Physics 2015-05-28 V. Botella-Soler , P. Glendinning

Random abstract simplicial complex representation provides a mathematical description of wireless networks and their topology. In order to reduce the energy consumption in this type of network, we intend to reduce the number of network…

Probability · Mathematics 2017-09-05 Anaïs Vergne , Laurent Decreusefond , Philippe Martins

We propose new direction to understanding evolutionary dynamics of complex networks using two different types of collaboration networks: academic collaboration networks; and, disaster collaboration networks. The results show that academic…

Social and Information Networks · Computer Science 2015-03-29 Alireza Abbasi , Liaquat Hossain , Rolf T Wigand

Despite being a source of rich information, graphs are limited to pairwise interactions. However, several real-world networks such as social networks, neuronal networks, etc., involve interactions between more than two nodes. Simplicial…

Data Analysis, Statistics and Probability · Physics 2022-02-01 Sanjukta Krishnagopal , Ginestra Bianconi

A large number of complex systems find a natural abstraction in the form of weighted networks whose nodes represent the elements of the system and the weighted edges identify the presence of an interaction and its relative strength. In…

Physics and Society · Physics 2009-04-23 M. Angeles Serrano , Marian Boguna , Alessandro Vespignani

It is common for people to access multiple social networks, for example, using phone, email, and social media. Together, the multi-layer social interactions form a "integrated social network." How can we extend well developed knowledge…

Social and Information Networks · Computer Science 2016-09-07 Kristina Lerman , Shang-Hua Teng , Xiaoran Yan

Natural and man-made transport webs are frequently dominated by dense sets of nested cycles. The architecture of these networks, as defined by the topology and edge weights, determines how efficiently the networks perform their function.…

Quantitative Methods · Quantitative Biology 2016-07-27 Carl D. Modes , Marcelo O. Magnasco , Eleni Katifori

In physics we often use very simple models to describe systems with many degrees of freedom, but it is not clear why or how this success can be transferred to the more complex biological context. We consider models for the joint…

Neurons and Cognition · Quantitative Biology 2024-12-06 Luisa Ramirez , William Bialek , Stephanie E. Palmer , David J. Schwab