Concept

Small-world network

Related publications (252)

A brief exposure to rightward prismatic adaptation changes resting-state network characteristics of the ventral attentional system

A brief session of rightward prismatic adaptation (R-PA) has been shown to alleviate neglect symptoms in patients with right hemispheric damage, very likely by switching hemispheric dominance of the ventral attentional network (VAN) from the right to the l ...

2020

Robust P2P Personalized Learning

Rachid Guerraoui, Yahya Benkaouz

Decentralized machine learning over peer-to-peer networks is very appealing for it enables to learn personalized models without sharing users data, nor relying on any central server. Peers can improve upon their locally trained model across a network graph ...

IEEE2020

Highlighting action and environmental component interactions using a network theory approach

Paolo Perona

In Environmental Impact Assessment (EIA), the either positive or negative impacts that specific N project actions might generate on a number M of environmental components are typically summarized in the form of Interaction Matrix (IM). This is an NxM tabul ...

2020

Local Tomography of Large Networks Under the Low-Observability Regime

Ali H. Sayed, Augusto José Rabelo Almeida Santos

This article studies the problem of reconstructing the topology of a network of interacting agents via observations of the state-evolution of the agents. We focus on the large-scale network setting with the additional constraint of partial observations, wh ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

A complex networks approach to traffic flow theory: measures and models

Leonardo Bellocchi

In this thesis, we developed a research direction that combines the theoretical concepts of complex networks with practical needs and applications in the field of transportation engineering. As a first objective we analyzed the phenomenon of congestion pr ...

EPFL2020

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

What graph neural networks cannot learn: depth vs width

Andreas Loukas

This paper studies the expressive power of graph neural networks falling within the message-passing framework (GNNmp). Two results are presented. First, GNNmp are shown to be Turing universal under sufficient conditions on their depth, width, node attribut ...

2020

Testing for Equivalence of Network Distribution Using Subgraph Counts

We consider that a network is an observation, and a collection of observed networks forms a sample. In this setting, we provide methods to test whether all observations in a network sample are drawn from a specified model. We achieve this by deriving the j ...

AMER STATISTICAL ASSOC2020

Graph Learning Under Partial Observability

Ali H. Sayed, Augusto José Rabelo Almeida Santos

Many optimization, inference, and learning tasks can be accomplished efficiently by means of decentralized processing algorithms where the network topology (i.e., the graph) plays a critical role in enabling the interactions among neighboring nodes. There ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Sparse coupled logistic regression to estimate co-activation and modulatory influences of brain regions

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Ye Tian

Accurate mapping of the functional interactions between remote brain areas with resting-state functional magnetic resonance imaging requires the quantification of their underlying dynamics. In conventional methodological pipelines, a spatial scale of inter ...

IOP PUBLISHING LTD2020

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