Zobrazeno 1 - 10
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pro vyhledávání: '"Serrano, M. P."'
Anatomical connectivity between different regions in the brain can be mapped to a network representation, the connectome, where the intensities of the links, the weights, influence its structural resilience and the functional processes it sustains. Y
Externí odkaz:
http://arxiv.org/abs/2410.06739
Autor:
Messina, S., Catanzaro, G., Lanza, A. F., Gandolfi, D., Serrano, M. M., Deeg, H. J., Garcia-Alvarez, D.
RACE-OC (Rotation and ACtivity Evolution in Open Clusters) is a project aimed at characterising the rotational and magnetic activity properties of the late-type members of open clusters, stellar associations, and moving groups of different ages. As p
Externí odkaz:
http://arxiv.org/abs/2408.16328
Graph Neural Networks (GNNs) have excelled in predicting graph properties in various applications ranging from identifying trends in social networks to drug discovery and malware detection. With the abundance of new architectures and increased comple
Externí odkaz:
http://arxiv.org/abs/2406.02772
The Renormalization Group is crucial for understanding systems across scales, including complex networks. Renormalizing networks via network geometry, a framework in which their topology is based on the location of nodes in a hidden metric space, is
Externí odkaz:
http://arxiv.org/abs/2403.12663
Publikováno v:
Journal of Computational and Applied Mathematics 404 (2022) 113121
Almost strictly sign regular matrices are sign regular matrices with a special zero pattern and whose nontrivial minors are nonzero. In this paper we provide several properties of almost strictly sign regular rectangular matrices and analyze their QR
Externí odkaz:
http://arxiv.org/abs/2402.10225
In existing models and embedding methods of networked systems, node features describing their qualities are usually overlooked in favor of focusing solely on node connectivity. This study introduces $FiD$-Mercator, a model-based ultra-low dimensional
Externí odkaz:
http://arxiv.org/abs/2401.09368
Geometry can be used to explain many properties commonly observed in real networks. It is therefore often assumed that real networks, especially those with high average local clustering, live in an underlying hidden geometric space. However, it has b
Externí odkaz:
http://arxiv.org/abs/2312.07416
Publikováno v:
NeuroImage, 297, 120703 (2024)
The architecture of the human connectome supports efficient communication protocols relying either on distances between brain regions or on the intensities of connections. However, none of these protocols combines information about the two or reaches
Externí odkaz:
http://arxiv.org/abs/2311.10669
Graph-structured data provide a comprehensive description of complex systems, encompassing not only the interactions among nodes but also the intrinsic features that characterize these nodes. These features play a fundamental role in the formation of
Externí odkaz:
http://arxiv.org/abs/2307.14198
The geometric renormalization technique for complex networks has successfully revealed the multiscale self-similarity of real network topologies and can be applied to generate replicas at different length scales. In this letter, we extend the geometr
Externí odkaz:
http://arxiv.org/abs/2307.00879