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Found 16 papers, 9 papers with code
Firing rate distributions in plastic networks of spiking neurons
In recurrent networks of leaky integrate-and-fire (LIF) neurons, mean-field theory has proven successful in describing various statistical properties of neuronal activity at equilibrium, such as firing rate distributions.
Temporal and probabilistic comparisons of epidemic interventions
Forecasting disease spread is a critical tool to help public health officials design and plan public health interventions. However, the expected future state of an epidemic is not necessarily well defined as disease spread is inherently stochastic, contact patterns within a population are heterogeneous, and behaviors change.
Exact and rapid linear clustering of networks with dynamic programming
We study the problem of clustering networks whose nodes have imputed or physical positions in a single dimension, for example prestige hierarchies or the similarity dimension of hyperbolic embeddings.
The network epidemiology of an Ebola epidemic
We leverage the data collected by the surveillance and contact tracing protocols of the Sierra Leone Ministry of Health and Sanitation, the US Centers for Disease Control and Prevention, and other responding partners to validate a network epidemiology framework connecting the population (incidence), community (local forecasts), and individual (secondary infections) scales of disease transmission.
Predicting the diversity of early epidemic spread on networks
We show how the challenge of inferring the early course of an epidemic falls on the randomness of disease spread more so than on the heterogeneity of contact patterns.
Universal nonlinear infection kernel from heterogeneous exposure on higher-order networks
The colocation of individuals in different environments is an important prerequisite for exposure to infectious diseases on a social network.
Physics and Society Adaptation and Self-Organizing Systems
Deep learning of contagion dynamics on complex networks
Forecasting the evolution of contagion dynamics is still an open problem to which mechanistic models only offer a partial answer.
Stochasticity and heterogeneity in the transmission dynamics of SARS-CoV-2
SARS-CoV-2 causing COVID-19 disease has moved rapidly around the globe, infecting millions and killing hundreds of thousands.
Social confinement and mesoscopic localization of epidemics on networks
Recommendations around epidemics tend to focus on individual behaviors, with much less efforts attempting to guide event cancellations and other collective behaviors since most models lack the higher-order structure necessary to describe large gatherings.
Physics and Society Adaptation and Self-Organizing Systems
Beyond $R_0$: Heterogeneity in secondary infections and probabilistic epidemic forecasting
Lastly, we demonstrate that without data on the heterogeneity in secondary infections for emerging infectious diseases like COVID-19, the uncertainty in outbreak size ranges dramatically.
Populations and Evolution Applied Physics Physics and Society
On the accuracy of message-passing approaches to percolation in complex networks
In fact we find that the closer a non-tree network is to a tree, the worse the MPA accuracy becomes.
Physics and Society Statistical Mechanics
Mercator: uncovering faithful hyperbolic embeddings of complex networks
We introduce Mercator, a reliable embedding method to map real complex networks into their hyperbolic latent geometry.
Smeared phase transitions in percolation on real complex networks
Our results shed light not only on the nature of the percolation transition in complex systems, but also provide two important insights on the numerical and analytical tools we use to study them.
Physics and Society Disordered Systems and Neural Networks
Percolation and the effective structure of complex networks
Analytical approaches to model the structure of complex networks can be distinguished into two groups according to whether they consider an intensive (e. g., fixed degree sequence and random otherwise) or an extensive (e. g., adjacency matrix) description of the network structure.
Physics and Society Statistical Mechanics
Navigable maps of structural brain networks across species
Using a decentralized navigation protocol, we investigate the relationship between the structure of the connectomes of different species and their spatial layout.
Multi-scale structure and topological anomaly detection via a new network statistic: The onion decomposition
The onion spectrum is exactly as easy to compute as the k-cores: It is based on the stages at which each vertex gets removed from a graph in the standard algorithm for computing the k-cores.
Physics and Society Disordered Systems and Neural Networks Discrete Mathematics Social and Information Networks Combinatorics
