Renaud Lambiotte

Publications : 207
Aldex : 100
H-index : 37
Citations : 5590


Local dominance unveils clusters in networks

Fan Shang, Ruiqi Li et 8 al.

Sep 30, 2022 in Arxiv
Clusters or communities can provide a coarse-grained description of complex systems at multiple scales, but their detection remains challenging in practice. Community detection methods often define communities as dense subgraphs, or subgraphs with few connections in-between, via concepts such as the cut, conductance, or modularity. Here we consider another perspective built on the notion of local ...

Discrete curvature on graphs from the effective resistance

Karel Devriendt, Renaud Lambiotte

Jan 17, 2022 in Arxiv
This article introduces a new approach to discrete curvature based on the concept of effective resistances. We propose a curvature on the nodes and links of a graph and present the evidence for their interpretation as a curvature. Notably, we find a relation to a number of well-established discrete curvatures (Ollivier, Forman, combinatorial curvature) and show evidence for convergence to continuo...

Unifying information propagation models on networks and influence maximization

Yu Tian, Renaud Lambiotte

Dec 2, 2021 in Arxiv
Information propagation on networks is a central theme in social, behavioral, and economic sciences, with important theoretical and practical implications, such as the influence maximization problem for viral marketing. Here, we consider a model that unifies the classical independent cascade models and the linear threshold models, and generalise them by considering continuous variables and allowin...

mathematics

Dynamics of majority rule on hypergraphs.

James Noonan, Renaud Lambiotte

Aug 1, 2021 in Physical review. E
A broad range of dynamical systems involve multibody interactions, or group interactions, which may not be encoded in traditional graphical structures. In this work, we focus on a canonical example from opinion dynamics, namely the majority rule, and we investigate the possibility to represent and analyze the system by means of hypergraphs. We explore the formation of consensus, and we restrict ou...

Entropy-based random models for hypergraphs

Fabio Saracco et 4 al.

Jul 21, 2022 in Arxiv
Network science has traditionally focused on pairwise relationships while disregarding many-body interactions. Hypergraphs are promising mathematical objects for the description of the latter ones. Here, we propose null models to analyse hypergraphs that generalise the classical Erd\"os-R\'enyi and Configuration Model by randomising incidence matrices in a constrained fashion. After discussing the...

Editorial: Scalable Network Generation & Analysis

Philippe J. Giabbanelli et 4 al.

Jul 25, 2022 in Frontiers in Big Data

physics

Metastable oscillatory modes emerge from synchronization in the brain spacetime connectome

Joana Cabral, Gustavo Deco et 8 al.

Jul 15, 2022 in Communications Physics

Gromov Centrality: A Multi-Scale Measure of Network Centrality Using Triangle Inequality Excess

Shazia'Ayn Babul et 3 al.

May 10, 2022 in Arxiv
Centrality measures quantify the importance of a node in a network based on different geometric or diffusive properties, and focus on different scales. Here, we adopt a geometrical viewpoint to define a multi-scale centrality in networks. Given a metric distance between the nodes, we measure the centrality of a node by its tendency to be close to geodesics between nodes in its neighborhood, via th...

Unifying information propagation models on networks and influence maximisation

Yu Tian, Renaud Lambiotte

Dec 2, 2021 in Arxiv
Information propagation on networks is a central theme in social, behavioural, and economic sciences, with important theoretical and practical implications, such as the influence maximisation problem for viral marketing. Here, we consider a model that unifies the classical independent cascade models and the linear threshold models, and generalise them by considering continuous variables and allowi...

Similar author:

Kurt Rothermel