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Concept

Centralité

Publications associées (25)

Scalable maximal subgraph mining with backbone-preserving graph convolutions

Karl Aberer, Thành Tâm Nguyên, Quoc Viet Hung Nguyen, Thanh Trung Huynh

Maximal subgraph mining is increasingly important in various domains, including bioinformatics, genomics, and chemistry, as it helps identify common characteristics among a set of graphs and enables their classification into different categories. Existing ...

ELSEVIER SCIENCE INC2023

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-constrained Cycles

Paolo Ienne, Kubilay Atasu, Jovan Blanusa

Cycles are one of the fundamental subgraph patterns and being able to enumerate them in graphs enables important applications in a wide variety of fields, including finance, biology, chemistry, and network science. However, to enable cycle enumeration in r ...

Assoc Computing Machinery2023

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-Constrained Cycles

Paolo Ienne, Kubilay Atasu, Jovan Blanusa

Finding cycles in directed graphs enables important applications in various domains such as finance, biology, chemistry, and network science. However, as the size of graph datasets continues to grow, it becomes increasingly difficult to discover cycles wit ...

arXiv2023

Motif Cut Sparsifiers

Mikhail Kapralov, Jakab Tardos, Mikhail Makarov

A motif is a frequently occurring subgraph of a given directed or undirected graph G (Milo et al.). Motifs capture higher order organizational structure of G beyond edge relationships, and, therefore, have found wide applications such as in graph clusterin ...

IEEE COMPUTER SOC2022

Information Retrieval Under Network Uncertainty: Robust Internet Ranking

Ralf Seifert, Anna Timonina-Farkas

Internet ranking algorithms play a crucial role in information technologies and numerical analysis due to their efficiency in high dimensions and wide range of possible applications, including scientometrics and systemic risk in finance (SinkRank, DebtRank ...

2023

ECCE: Entity-centric Corpus Exploration Using Contextual Implicit Networks

Maud Ehrmann, Matteo Romanello, Andreas Oliver Spitz

In the Digital Age, the analysis and exploration of unstructured document collections is of central importance to members of investigative professions, whether they might be scholars, journalists, paralegals, or analysts. In many of their domains, entities ...

ACM Digital Press2022

Generation of elastic geodesic gridshells with anisotropic cross sections

Corentin Jean Dominique Fivet, Nicolas Robin Montagne

Geodesic gridshells are shell structures made of continuous elements following geodesic lines. Their properties ease the use of beams with anisotropic cross-sections by avoiding bending about their strong axis. However, such bending may arise when flatteni ...

2021

Switchover phenomenon induced by epidemic seeding on geometric networks

Gergely Odor

It is a fundamental question in disease modeling how the initial seeding of an epidemic, spreading over a network, determines its final outcome. One important goal has been to find the seed configuration, which infects the most individuals. Although the id ...

2021

Scale-dependent measure of network centrality from diffusion dynamics

Alexis Arnaudon

Classic measures of graph centrality capture distinct aspects of node importance, from the local (e.g., degree) to the global (e.g., closeness). Here we exploit the connection between diffusion and geometry to introduce a multiscale centrality measure. A n ...

AMER PHYSICAL SOC2020

Simplicity in complex networks: a path-based centrality

Nikolaos Geroliminis, Leonardo Bellocchi

Understanding travel behaviour in transportation system is key challenge to calibrate and simulate the usage of urban mobility networks. We define in this work a path-based centrality based on the simplicity of the path between two locations in road networ ...

2020

Systemic Risk in Networks with a Central Node

Damir Filipovic, Léo Hamed Amini

We examine the effects on a financial network of clearing all contracts though a central node (CN), thereby transforming the original network into a star-shaped one. The CN is capitalized with external equity and a guaranty fund. We introduce a structural ...

SIAM PUBLICATIONS2020

A Measure of Dynamical Efficiency for Multimodal Interconnected Urban Systems

Nikolaos Geroliminis, Leonardo Bellocchi

Complex network theory describes network performance mostly based on topological characteristics, like betweenness centrality. This work integrates concepts from complex networks and traffic engineering. We propose a new measure for spatial networks and, i ...

2020

The diagnostic potential of multimodal neuroimaging measures in Parkinson's disease and atypical parkinsonism

Chang-Hyun Park

Introduction For the diagnosis of Parkinson's disease (PD) and atypical parkinsonism (AP) using neuroimaging, structural measures have been largely employed since structural abnormalities are most noticeable in the diseases. Functional abnormalities have b ...

2020

The key player problem in complex oscillator networks and electric power grids: Resistance centralities identify local vulnerabilities

Philippe René Joseph Jacquod, Melvyn Sandy Tyloo

Identifying key players in coupled individual systems is a fundamental problem in network theory. We investigate synchronizable network-coupled dynamical systems such as high-voltage electric power grids and coupled oscillators on complex networks. We defi ...

2019

Global robustness versus local vulnerabilities in complex synchronous networks

Philippe René Joseph Jacquod

In complex network-coupled dynamical systems, two questions of central importance are how to identify the most vulnerable components and how to devise a network making the overall system more robust to external perturbations. To address these two questions ...

2019

Percolation and Internet Science

Emanuele Massaro

Percolation, in its most general interpretation, refers to the “flow” of something (a physical agent, data or information) in a network, possibly accompanied by some nonlinear dynamical processes on the network nodes (sometimes denoted reaction–diffusion s ...

2019

Graph Learning with Partial Observations: Role of Degree Concentration

Ali H. Sayed, Augusto José Rabelo Almeida Santos

In this work we consider the problem of learning an Erdos-Renyi graph over a diffusion network when: i) data from only a limited subset of nodes are available (partial observation); ii) and the inferential goal is to discover the graph of interconnections ...

IEEE2019

Actuation Displacement Analysis of a Self-Switching Shape Memory Alloy Buckled Beam

Yves Perriard, Yoan René Cyrille Civet, Morgan Almanza, Sean Thomas

This paper aims to simulate using Finite Element Modelling (FEM), a self-activating bistable buckled beam actuator using SMAs. In this work, various parameters such as the dimensions of the beam, shape geometry are studied to determine their effects on the ...

2018

Nuove ecologie alpine: industrializzazione e costruzione della città-territorio

Roberto Sega

This research study offers a reflection on the Alpine urban condition through the observation of the spaces of production. Departing from the premise that the tourist economy cannot be the only possible horizon for Alpine development, this thesis reflects ...

EPFL2018

Localizing the Source of an Epidemic Using Few Observations

Brunella Marta Spinelli

Localizing the source of an epidemic is a crucial task in many contexts, including the detection of malicious users in social networks and the identification of patient zeros of disease outbreaks. The difficulty of this task lies in the strict limitation ...

EPFL2018