Structure and dynamical behavior of non-normal networks de réir Asllani, M, Lambiotte, R, Carletti, T

“…We analyze a collection of empirical networks in a wide spectrum of disciplines and show that strong non-normality is ubiquitous in network science. Dynamical processes evolving on non-normal networks exhibit a peculiar behavior, as initial small disturbances may undergo a transient phase and be strongly amplified in linearly stable systems. …”

Inferring mechanisms for global constitutional progress

“…We make use of techniques from network science and information retrieval to quantify and compare temporal and network effects on constitutional change, which have been the focus of previous work. …”
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Friends recommendation on social networks de réir Rahman Syukri Othman

“…Unlike existing techniques like collaborative filtering that are widely utilized in recommender systems, this project will investigate the recommendation problem from the perspective of network science. To be specific, a social network will first be modeled as a temporal graph, then link prediction technique and its variants will be explored for calculating the probability for any pair of unconnected nodes to be connected. …”
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A Matrix Iteration for Dynamic Network Summaries. de réir Grindrod, P, Higham, D

“…This allows us to generalize widely used Katz-style centrality measures that have proved popular in network science to the case of dynamic networks sampled at nonuniform points in time. …”

Circular specifications and “predicting” with information from the future: Errors in the empirical SAOM–TERGM comparison of Leifeld & Cranmer de réir Block, P, Hollway, J, Stadtfeld, C, Koskinen, J, Snijders, T

“…We review the empirical comparison of Stochastic Actor-oriented Models (SAOMs) and Temporal Exponential Random Graph Models (TERGMs) by Leifeld & Cranmer in this journal [Network Science 7(1):20–51, 2019]. When specifying their TERGM, they use exogenous nodal attributes calculated from the outcome networks’ observed degrees instead of endogenous ERGM equivalents of structural effects as used in the SAOM. …”

Dunbar’s number(s): constraints on the social world de réir Dunbar, R

“…It is widely cited throughout the social sciences, archaeology, psychology and network science, and its reverberations have been felt as far afield as the worlds of business organization and social-networking sites, whose design it has come to underpin. …”

Asynchronous Approximation of a Single Component of the Solution to a Linear System de réir Ozdaglar, Asuman E., Shah, Devavrat, Yu, Christina Lee

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Quantifying reputation and success of data scientists de réir Soh, Isaac Wei Yang

“…This project exploits network science techniques to understand and predict success of data scientist. …”
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Dynamical clustering of exchange rates de réir Fenn, D, Porter, M, Mucha, P, McDonald, M, Williams, S, Johnson, N, Jones, N

“…We use techniques from network science to study correlations in the foreign exchange (FX) market during the period 1991-2008. …”

High modularity creates scaling laws de réir Grindrod, P, Higham, D

“…In this work, we use network science and dynamical systems perspectives to explain that the observed scaling laws, and power laws in particular, arise naturally when some feature of a complex system is measured in terms of the system size. …”

Great expectations: using whole-brain computational connectomics for understanding neuropsychiatric disorders de réir Deco, G, Kringelbach, M

“…The study of human brain networks with in vivo neuroimaging has given rise to the field of connectomics, furthered by advances in network science and graph theory informing our understanding of the topology and function of the healthy brain. …”

Multislice modularity optimization in community detection and image segmentation de réir Hu, H, Van Gennip, Y, Hunter, B, Bertozzi, A, Porter, M

“…One of the most important areas of network science is the algorithmic detection of cohesive groups (i.e., "communities") of nodes. …”

Inferring mechanisms for global constitutional progress de réir Rutherford, Alex, Lupu, Yonatan, Cebrian, Manuel, Rahwan, Iyad, LeVeck, Brad, Garcia-Harranz, Manuel

“…We make use of techniques from network science and information retrieval to quantify and compare temporal and network effects on constitutional change, which have been the focus of previous work. …”
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Semi supervised learning with graph convolutional networks de réir Ong, Jia Rui

“…In this report, we present the first comparative study between Graph Convolutional Networks (GCNs), Residual Gated Graph ConvNets (RGGCNs) and Graph Attention Networks (GATs), on two fundamental tasks in network science, semi-supervised classification and semi-supervised clustering, to analyse their experimental performances. …”
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From time series to networks in R with the ts2net package de réir Ferreira, LN

“…Network science established itself as a prominent tool for modeling time series and complex systems. …”

Robustness of coupled networks with multiple support from functional components at different scales de réir Dong, G, Sun, N, Yan, M, Wang, F, Lambiotte, R

“…Robustness is an essential component of modern network science. Here, we investigate the robustness of coupled networks where the functionality of a node depends not only on its connectivity, here measured by the size of its connected component in its own network, but also the support provided by at least M links from another network. …”

Dynamic network centrality summarizes learning in the human brain de réir Mantzaris, A, Bassett, D, Wymbs, N, Estrada, E, Porter, M, Mucha, P, Grafton, S

“…We study functional activity in the human brain using functional magnetic resonance imaging and recently developed tools from network science. The data arise from the performance of a simple behavioural motor learning task. …”

Structural balance and random walks on complex networks with complex weights de réir Tian, Y, Lambiotte, R

“…Recent years have seen an increasing interest to extend the tools of network science when the weight of edges are complex numbers. …”

Flux-dependent graphs for metabolic networks de réir Beguerisse-Díaz, M, Bosque, G, Oyarzún, D, Picó, J, Barahona, M

“…By integrating constraint-based models and tools from network science, our framework allows the study of context-specific metabolic responses at a system level beyond standard pathway descriptions.…”

Graph signal processing for machine learning: a review and new perspectives de réir Dong, X, Thanou, D, Toni, L, Bronstein, M, Frossard, P

“…Furthermore, we provide new perspectives on the future development of GSP techniques that may serve as a bridge between applied mathematics and signal processing on one side and machine learning and network science on the other. Cross-fertilization across these different disciplines may help unlock the numerous challenges of complex data analysis in the modern age.…”