Publications related to Character network analysis of Émile Zola’s Les Rougon-Macquart

Privacy-Preserving Machine Learning on Graphs

Graph Neural Networks (GNNs) have emerged as a powerful tool for learning on graphs, demonstrating exceptional performance in various domains. However, as GNNs become increasingly popular, new challenges arise. One of the most pressing is the need to ensur ...

EPFL2023

Maintenance scheduling of manufacturing systems based on optimal price of the network

Olga Fink

Goods can exhibit positive externalities impacting decisions of customers in social networks. Suppliers can integrate these externalities in their pricing strategies to increase their revenue. Besides optimizing the prize, suppliers also have to consider t ...

2022

The Paris/Geneva Divide. A Network Analysis of the Archives of the International Committee on Intellectual Cooperation of the League of Nations

The International Committee on Intellectual Cooperation (ICIC) is often framed as a step in the constitution of a “League of Minds” – a place where scientists and writers reign, and a necessary part of a successful and harmonious “League of Nations” – but ...

De Gruyter2022

Opinion Formation over Adaptive Networks

Virginia Bordignon

An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...

EPFL2022

Investigating cognitive ability using action-based models of structural brain networks

Enrico Amico

Recent developments in network neuroscience have highlighted the importance of developing techniques for analysing and modelling brain networks. A particularly powerful approach for studying complex neural systems is to formulate generative models that use ...

OXFORD UNIV PRESS2022

True scale-free networks hidden by finite size effects

Andrea Rinaldo, Samir Suweis, Amos Maritan

We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statisti ...

National Academy of Sciences2021

The physics of higher-order interactions in complex systems

Enrico Amico, Benedetta Franceschiello

Network representations of complex systems are limited to pairwise interactions, but real-world systems often involve higher-order interactions. This Perspective looks at the new physics emerging from attempts to characterize these interactions. ...

NATURE PORTFOLIO2021

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing

Dimitri Nestor Alice Van De Ville, Maude Schneider, Anjali Bagunu Tarun, Daniela Maria Zöller

Causal interactions between specific psychiatric symptoms could contribute to the heterogenous clinical trajectories observed in early psychopathology. Current diagnostic approaches merge clinical manifestations that co-occur across subjects and could sign ...

eLIFE SCIENCES PUBL LTD2021

Multilayer Graph Clustering With Optimized Node Embedding

Pascal Frossard, Mireille El Gheche

We are interested in multilayer graph clustering, which aims at dividing the graph nodes into categories or communities. To do so, we propose to learn a clustering-friendly embedding of the graph nodes by solving an optimization problem that involves a fid ...

IEEE2021

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

MPGM: Scalable and Accurate Multiple Network Alignment

Matthias Grossglauser, Ehsan Kazemi

Protein-protein interaction (PPI) network alignment is a canonical operation to transfer biological knowledge among species. The alignment of PPI-networks has many applications, such as the prediction of protein function, detection of conserved network mot ...

IEEE COMPUTER 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

Léo Hamed Amini, Damir Filipovic

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

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion

Jean-Marc Odobez, Olivier Canévet, Michael Villamizar

We present an efficient and accurate people detection approach based on deep learning to detect people attacks and intrusion in video surveillance scenarios Unlike other approaches using background segmentation and pre-processing techniques, which are not ...

2020

Exploring dynamic functional connectivity by incorporating prior knowledge of brain structure

Anjali Bagunu Tarun

The synchronized firing of distant neuronal populations gives rise to a wide array of functional brain networks that underlie human brain function. Given the enormous perception, learning, and cognition potential of the human brain, it is not surprising th ...

EPFL2020

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

Network Alignment by Representation Learning on Structure and Attribute

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong, Thanh Trung Huynh

Network alignment is the task of recognizing similar network nodes across different networks, which has many applications in various domains. As traditional network alignment methods based on matrix factorization do not scale to large graphs, a variety of ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

How single neuron properties shape chaotic dynamics and signal transmission in random neural networks

Wulfram Gerstner, Tilo Schwalger, Samuel Pavio Muscinelli

While most models of randomly connected neural networks assume single-neuron models with simple dynamics, neurons in the brain exhibit complex intrinsic dynamics over multiple timescales. We analyze how the dynamical properties of single neurons and recurr ...

2019

A Dynamic Embedding Model of the Media Landscape

Karl Aberer, Jérémie Rappaz

Information about world events is disseminated through a wide variety of news channels, each with specific considerations in the choice of their reporting. Although the multiplicity of these outlets should ensure a variety of viewpoints, recent reports sug ...

ASSOC COMPUTING MACHINERY2019