Search Results for author:
Found 11 papers, 2 papers with code
Topological conditions drive stability in meta-ecosystems
On a global level, ecological communities are being perturbed at an unprecedented rate by human activities and environmental instabilities.
The resilience of the multirelational structure of geopolitical treaties is critically linked to past colonial world order and offshore fiscal havens
The governance of the political and economic world order builds on a complex architecture of international treaties at various geographical scales.
The political economy of big data leaks: Uncovering the skeleton of tax evasion
After the leak of 11. 5 million documents from the Panamanian corporation Mossack Fonseca, an intricate network of offshore business entities has been revealed.
mGNN: Generalizing the Graph Neural Networks to the Multilayer Case
Networks are a powerful tool to model complex systems, and the definition of many Graph Neural Networks (GNN), Deep Learning algorithms that can handle networks, has opened a new way to approach many real-world problems that would be hardly or even untractable.
Machine learning dismantling and early-warning signals of disintegration in complex systems
From physics to engineering, biology and social science, natural and artificial systems are characterized by interconnected topologies whose features - e. g., heterogeneous connectivity, mesoscale organization, hierarchy - affect their robustness to external perturbations, such as targeted attacks to their units.
Network Geometry
Networks are natural geometric objects.
Physics and Society Disordered Systems and Neural Networks Social and Information Networks
Unraveling the hidden organisation of urban systems and their mobility flows
Increasing evidence suggests that cities are complex systems, with structural and dynamical features responsible for a broad spectrum of emerging phenomena.
Physics and Society Disordered Systems and Neural Networks
Distance entropy cartography characterises centrality in complex networks
We introduce distance entropy as a measure of homogeneity in the distribution of path lengths between a given node and its neighbours in a complex network.
Convolutional neural networks for structured omics: OmicsCNN and the OmicsConv layer
Convolutional Neural Networks (CNNs) are a popular deep learning architecture widely applied in different domains, in particular in classifying over images, for which the concept of convolution with a filter comes naturally.
Multiplex model of mental lexicon reveals explosive learning in humans
Our findings provide quantitative confirmation of existing conjectures about core structure in the mental lexicon and the importance of integrating multi-relational word-word interactions in psycholinguistic frameworks.
Diffusion geometry unravels the emergence of functional clusters in collective phenomena
Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their inter-connectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us.
