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Quantification of symmetries in complex networks is typically done globally in terms of automorphisms. Extending previous methods to locally assess the symmetry of nodes is not straightforward. Here we present a new framework to quantify…

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely…

Physics and Society · Physics 2012-06-11 Stefano Cardanobile , Volker Pernice , Moritz Deger , Stefan Rotter

Hyperuniformity, which is a type of long-range order that is characterized by the suppression of long-range density fluctuations in comparison to the fluctuations in standard disordered systems, has emerged as a powerful concept to aid in…

Disordered Systems and Neural Networks · Physics 2025-12-19 James V. Raj , Xiaohan Sun , Charles Emmett Maher , Katherine A. Newhall , Mason A. Porter

We recently introduced a formalism for the modeling of temporal networks, that we call stream graphs. It emphasizes the streaming nature of data and allows rigorous definitions of many important concepts generalizing classical graphs. This…

Social and Information Networks · Computer Science 2021-11-24 Matthieu Latapy , Clémence Magnien , Tiphaine Viard

The coarse Ricci curvature of graphs introduced by Ollivier as well as its modification by Lin-Lu-Yau have been studied from various aspects. In this paper, we propose a new transport distance appropriate for hypergraphs and study a…

Metric Geometry · Mathematics 2022-06-07 Tomoya Akamatsu

Bridging geometry and topology, curvature is a powerful and expressive invariant. While the utility of curvature has been theoretically and empirically confirmed in the context of manifolds and graphs, its generalization to the emerging…

Machine Learning · Computer Science 2023-04-07 Corinna Coupette , Sebastian Dalleiger , Bastian Rieck

Many of the structural characteristics of a network depend on the connectivity with and within the hubs. These dependencies can be related to the degree of a node and the number of links that a node shares with nodes of higher degree. In…

Physics and Society · Physics 2018-10-31 Raul J Mondragon

Over the last decade, random hyperbolic graphs have proved successful in providing geometric explanations for many key properties of real-world networks, including strong clustering, high navigability, and heterogeneous degree…

Physics and Society · Physics 2023-03-01 Béatrice Désy , Patrick Desrosiers , Antoine Allard

A new type of sectional curvature is introduced. The notion is purely algebraic and can be located in linear algebra as well as in differential geometry.

Differential Geometry · Mathematics 2015-04-07 Barbara Opozda

One property of networks that has received comparatively little attention is hierarchy, i.e., the property of having vertices that cluster together in groups, which then join to form groups of groups, and so forth, up through all levels of…

Physics and Society · Physics 2008-04-12 Aaron Clauset , Cristopher Moore , M. E. J. Newman

The curvature regularities are well-known for providing strong priors in the continuity of edges, which have been applied to a wide range of applications in image processing and computer vision. However, these models are usually non-convex,…

Numerical Analysis · Mathematics 2019-12-03 Qiuxiang Zhong , Ke Yin , Yuping Duan

We explore the notion of m-intermediate Ricci curvature assumption introduced by Brendle-Hirsch-Johne further. If a manifold has non-negative m-intermediate Ricci curvature and stable weighted slicing of order m-1, then the last slice has…

Differential Geometry · Mathematics 2025-10-14 Yujie Wu

A complex network approach on a rough fracture is developed. In this manner, some hidden metric spaces (similarity measurements) between apertures profiles are set up and a general evolutionary network in two directions (in parallel and…

Adaptation and Self-Organizing Systems · Physics 2009-05-12 H. O. Ghaffari , M. Sharifzadeh , M. Fall , E. Evgin

Deep Learning methods, specifically convolutional neural networks (CNNs), have seen a lot of success in the domain of image-based data, where the data offers a clearly structured topology in the regular lattice of pixels. This…

Machine Learning · Statistics 2018-05-31 Thomas Teh , Chaiyawan Auepanwiriyakul , John Alexander Harston , A. Aldo Faisal

Network models with latent geometry have been used successfully in many applications in network science and other disciplines, yet it is usually impossible to tell if a given real network is geometric, meaning if it is a typical element in…

Statistical Mechanics · Physics 2016-05-23 Dmitri Krioukov

Graph data often exhibits complex geometric heterogeneity, where structures with varying local curvature, such as tree-like hierarchies and dense communities, coexist within a single network. Existing geometric GNNs, which embed graphs into…

Machine Learning · Computer Science 2026-01-21 Xudong Wang , Chris Ding , Tongxin Li , Jicong Fan

Let $M$ denote a low-dimensional manifold embedded in Euclidean space and let ${X}= \{ x_1, \dots, x_n \}$ be a collection of points uniformly sampled from it. We study the relationship between the curvature of a random geometric graph…

Differential Geometry · Mathematics 2024-08-27 Nicolas Garcia Trillos , Melanie Weber

The integrated mean curvature of a simplicial manifold is well understood in both Regge Calculus and Discrete Differential Geometry. However, a well motivated pointwise definition of curvature requires a careful choice of volume over which…

General Relativity and Quantum Cosmology · Physics 2016-03-21 Rory Conboye , Warner A. Miller , Shannon Ray

A vast variety of biological, social, and economical networks shows topologies drastically differing from random graphs; yet the quantitative characterization remains unsatisfactory from a conceptual point of view. Motivated from the…

Molecular Networks · Quantitative Biology 2010-03-11 Jens Christian Claussen

Complex networks can be used to represent complex systems which originate in the real world. Here we study a transformation of these complex networks into simplicial complexes, where cliques represent the simplices of the complex. We extend…

Social and Information Networks · Computer Science 2017-09-04 Ernesto Estrada , Grant Ross
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