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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 ...
Background: Functional neurological disorders were historically regarded as the manifestation of a dynamic brain lesion which might be linked to trauma or stress, although this association has not yet been directly tested yet. Analysing large-scale brain n ...
The integrations of advanced metering infrastructure and smart meters make it possible to detect electricity thieves by analyzing electricity consumption readings. However, the detection accuracies of traditional models are limited due to their difficulty ...
This work proposes a multi-agent filtering algorithm over graphs for finite-state hidden Markov models (HMMs), which can be used for sequential state estimation or for tracking opinion formation over dynamic social networks. We show that the difference fro ...
With the aim of improving trajectory estimation and point cloud georeferencing in the scope of Kinematic Laser Scanning (ALS), we recently proposed a novel procedure leveraging the automated extraction of reliable 3D point to point correspondences and thei ...
This work addresses the problem of learning the topology of a network from the signals emitted by the network nodes. These signals are generated over time through a linear diffusion process, where neighboring nodes exchange messages according to the underl ...
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 ...
While the idea of technology as a driving force of history and society has been extensively studied in the history of the Industrial Revolutions, little attention has been paid to the social perception of those technologies. This thesis focuses on the disc ...
Network alignment is the task of identifying topologically and semantically similar nodes across (two) different networks. It plays an important role in various applications ranging from social network analysis to bioinformatic network interactions. Howeve ...
Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Several methods have been proposed for the analysis of multivar ...