222 citations · 1.3k across the 45 of their papers we have counts for
14 papers · 1 filter
Predictability of Human Movements across Industry Sectors using Multilayer Networks
Maisha Islam Sejunti, Melissa Butler, Yingjie Hu +1
Predicting the patterns of human movement is important to applications from urban design to disease control and emergency response. In this work, we leverage machine learning (ML)…
Optimality as a Generative Principle for Network Structure
Guram Mikaberidze, Beso Mikaberidze, Dane Taylor
Most real-world networks have evolved or been engineered to optimize some function, yet a unified framework for studying optimal networks across domains is lacking. We introduce Gr…
Multilayer networks characterize human-mobility patterns by industry sector for the 2021 Texas winter storm
Melissa Butler, Alisha Khan, Francis Osei Tutu Afrifa +2
Understanding human mobility during disastrous events is crucial for emergency planning and disaster management. We develop a methodology to construct time-varying, multilayer netw…
A Parrondo paradox in susceptible-infectious-susceptible dynamics over periodic temporal networks
Maisha Islam Sejunti, Dane Taylor, Naoki Masuda
Many social and biological networks periodically change over time with daily, weekly, and other cycles. Thus motivated, we formulate and analyze susceptible-infectious-susceptible…
Ranking Edges by their Impact on the Spectral Complexity of Information Diffusion over Networks
Jeremy Kazimer, Manlio de Domenico, Peter J. Mucha +1
Despite the numerous ways now available to quantify which parts or subsystems of a network are most important, there remains a lack of centrality measures that are related to the c…
Balanced Hodge Laplacians Optimize Consensus Dynamics over Simplicial Complexes
Cameron Ziegler, Per Sebastian Skardal, Haimonti Dutta +1
Despite the vast literature on network dynamics, we still lack basic insights into dynamics on higher-order structures (e.g., edges, triangles, and more generally, -dimensional…
Coupling Asymmetry Optimizes Collective Dynamics over Multiplex Networks
Zhao Song, Dane Taylor
Networks are often interconnected, with one system wielding greater influence over another. However, the effects of such asymmetry on self-organized phenomena (e.g., consensus and…
Multiplex Markov Chains: Convection Cycles and Optimality
Dane Taylor
Multiplex networks are a common modeling framework for interconnected systems and multimodal data, yet we still lack fundamental insights for how multiplexity affects stochastic pr…
Case studies in network community detection
Saray Shai, Natalie Stanley, Clara Granell +2
Community structure describes the organization of a network into subgraphs that contain a prevalence of edges within each subgraph and relatively few edges across boundaries betwee…
Network-ensemble comparisons with stochastic rewiring and von Neumann entropy
Zichao Li, Peter J. Mucha, Dane Taylor
Assessing whether a given network is typical or atypical for a random-network ensemble (i.e., network-ensemble comparison) has widespread applications ranging from null-model selec…
Enhanced detectability of community structure in multilayer networks through layer aggregation
Dane Taylor, Saray Shai, Natalie Stanley +1
Many systems are naturally represented by a multilayer network in which edges exist in multiple layers that encode different, but potentially related, types of interactions, and it…
Eigenvector-Based Centrality Measures for Temporal Networks
Dane Taylor, Sean A. Myers, Aaron Clauset +2
Numerous centrality measures have been developed to quantify the importances of nodes in time-independent networks, and many of them can be expressed as the leading eigenvector of…
Social Climber attachment in forming networks produces phase transition in a measure of connectivity
Dane Taylor, Daniel B. Larremore
Formation and fragmentation of networks is typically studied using percolation theory, but most previous research has been restricted to studying a phase transition in cluster size…
Network connectivity during mergers and growth: optimizing the addition of a module
Dane Taylor, Juan G. Restrepo
The principal eigenvalue of a network's adjacency matrix often determines dynamics on the network (e.g., in synchronization and spreading processes) and some of its structural…