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pro vyhledávání: '"real-world networks"'
The wireless spectrum's increasing complexity poses challenges and opportunities, highlighting the necessity for real-time solutions and robust data processing capabilities. Digital Twin (DT), virtual replicas of physical systems, integrate real-time
Externí odkaz:
http://arxiv.org/abs/2411.03503
Autor:
Meghanathan, Natarajan
Exploratory factor analysis (EFA) is useful to identify the number and mapping of the hidden factors that could dominantly represent the features in the dataset. Principal component analysis (PCA) is the first step as part of the two-step procedure t
Externí odkaz:
http://arxiv.org/abs/2403.03525
Real-world network datasets are typically obtained in ways that fail to capture all edges. The patterns of missing data are often non-uniform as they reflect biases and other shortcomings of different data collection methods. Nevertheless, uniform mi
Externí odkaz:
http://arxiv.org/abs/2401.15140
Autor:
John, Jisha Mariyam1 (AUTHOR) jishamariyam.phd201010@iiitkottayam.ac.in, Bellingeri, Michele2,3 (AUTHOR) davide.cassi@unipr.it, Lekha, Divya Sindhu1 (AUTHOR) divyaslekha@iiitkottayam.ac.in, Cassi, Davide2,3 (AUTHOR) roberto.alfieri@unipr.it, Alfieri, Roberto2,3 (AUTHOR)
Publikováno v:
Mathematics (2227-7390). May2024, Vol. 12 Issue 10, p1568. 16p.
Autor:
Jiang, Xiangjian, Pu, Yanyi
Dynamic Graph Neural Networks (DGNNs) have emerged as the predominant approach for processing dynamic graph-structured data. However, the influence of temporal information on model performance and robustness remains insufficiently explored, particula
Externí odkaz:
http://arxiv.org/abs/2311.12255
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Autor:
Ghavasieh, Arsham, De Domenico, Manlio
Empirical complex systems must differentially respond to external perturbations and, at the same time, internally distribute information to coordinate their components. While networked backbones help with the latter, they limit the components' indivi
Externí odkaz:
http://arxiv.org/abs/2305.05975
The emergence of order in nature manifests in different phenomena, with synchronization being one of the most representative examples. Understanding the role played by the interactions between the constituting parts of a complex system in synchroniza
Externí odkaz:
http://arxiv.org/abs/2306.00237
Detecting the dimensionality of graphs is a central topic in machine learning. While the problem has been tackled empirically as well as theoretically, existing methods have several drawbacks. On the one hand, empirical tools are computationally heav
Externí odkaz:
http://arxiv.org/abs/2302.06357