Results 31 to 40 of about 31,893 (252)
Multiplex network infomax: Multiplex network embedding via information fusion
Digital Communications and Networks, 2023 For networking of big data applications, an essential issue is how to represent networks in vector space for further mining and analysis tasks, e.g., node classification, clustering, link prediction, and visualization. Most existing studies on this subject mainly concentrate on monoplex networks considering a single type of relation among nodes ...
Qiang Wang 0027 +5 more
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Inverse Percolation to Quantify Robustness in Multiplex Networks
Complexity, 2020 Inverse percolation is known as the problem of finding the minimum set of nodes whose elimination of their links causes the rupture of the network. Inverse percolation has been widely used in various studies of single-layer networks. However, the use and
Edwin Montes-Orozco +6 more
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Internetwork connectivity of molecular networks across species of life
Scientific Reports, 2021 Molecular interactions are studied as independent networks in systems biology. However, molecular networks do not exist independently of each other. In a network of networks approach (called multiplex), we study the joint organization of transcriptional ...
Tarun Mahajan, Roy D. Dar
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CS-MLGCN: Multiplex Graph Convolutional Networks for Community Search in Multiplex Networks
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022 Community Search (CS) is one of the fundamental tasks in network science and has attracted much attention due to its ability to discover personalized communities with a wide range of applications. Given any query nodes, CS seeks to find a densely connected subgraph containing query nodes.
Ali Behrouz, Farnoosh Hashemi
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Multi-scale asynchronous belief percolation model on multiplex networks
New Journal of Physics, 2019 The studies of multiplex networks are increasingly popular in recent years. Modeling multiple complex systems as a multiplex network has refreshed our understanding about the structure and dynamics of various real-world systems.
Hui-Jia Li, Lin Wang
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Cross-diffusion on multiplex networks
New Journal of Physics, 2020 During the past decades, pattern formulation with reaction–diffusion systems has attracted great research interest. Complex networks, from single-layer networks to more complicated multiplex networks, have made great contribution to the development of ...
Shupeng Gao +5 more
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Centrality in earthquake multiplex networks
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2018 Seismic time series has been mapped as a complex network, where a geographical region is divided into square cells that represent the nodes and connections are defined according to the sequence of earthquakes. In this paper, we map a seismic time series to a temporal network, described by a multiplex network, and characterize the evolution of the ...
Nastaran Lotfi +2 more
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Bandit Sampling for Multiplex Networks
CoRR, 2022 Graph neural networks have gained prominence due to their excellent performance in many classification and prediction tasks. In particular, they are used for node classification and link prediction which have a wide range of applications in social networks, biomedical data sets, and financial transaction graphs.
Cenk Baykal +3 more
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The Multiplex Dependency Structure of Financial Markets
Complexity, 2017 We propose here a multiplex network approach to investigate simultaneously different types of dependency in complex datasets. In particular, we consider multiplex networks made of four layers corresponding, respectively, to linear, nonlinear, tail, and ...
Nicolò Musmeci +4 more
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Spreading of memes on multiplex networks
New Journal of Physics, 2019 A model for the spreading of online information or "memes" on multiplex networks is introduced and analyzed using branching-process methods. The model generalizes that of [Gleeson et al., Phys.Rev. X., 2016] in two ways. First, even for a monoplex (single-layer) network, the model is defined for any specific network defined by its adjacency matrix ...
Joseph D O’Brien +2 more
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