Adaptive dynamical networks
It is a fundamental challenge to understand how the function of a network is related to its
structural organization. Adaptive dynamical networks represent a broad class of systems that …
structural organization. Adaptive dynamical networks represent a broad class of systems that …
Statistical inference links data and theory in network science
The number of network science applications across many different fields has been rapidly
increasing. Surprisingly, the development of theory and domain-specific applications often …
increasing. Surprisingly, the development of theory and domain-specific applications often …
Controlling complex networks with complex nodes
Real-world networks often consist of millions of heterogenous elements that interact at
multiple timescales and length scales. The fields of statistical physics and control theory both …
multiple timescales and length scales. The fields of statistical physics and control theory both …
[HTML][HTML] Surrogate data for hypothesis testing of physical systems
The availability of time series of the evolution of the properties of physical systems is
increasing, stimulating the development of many novel methods for the extraction of …
increasing, stimulating the development of many novel methods for the extraction of …
Dynamics of information diffusion and its applications on complex networks
The ongoing rapid expansion of the Word Wide Web (WWW) greatly increases the
information of effective transmission from heterogeneous individuals to various systems …
information of effective transmission from heterogeneous individuals to various systems …
Data based identification and prediction of nonlinear and complex dynamical systems
The problem of reconstructing nonlinear and complex dynamical systems from measured
data or time series is central to many scientific disciplines including physical, biological …
data or time series is central to many scientific disciplines including physical, biological …
Network reconstruction and community detection from dynamics
We present a scalable nonparametric Bayesian method to perform network reconstruction
from observed functional behavior that at the same time infers the communities present in …
from observed functional behavior that at the same time infers the communities present in …
Full reconstruction of simplicial complexes from binary contagion and Ising data
Previous efforts on data-based reconstruction focused on complex networks with pairwise or
two-body interactions. There is a growing interest in networks with higher-order or many …
two-body interactions. There is a growing interest in networks with higher-order or many …
Predicting network dynamics without requiring the knowledge of the interaction graph
A network consists of two interdependent parts: the network topology or graph, consisting of
the links between nodes and the network dynamics, specified by some governing equations …
the links between nodes and the network dynamics, specified by some governing equations …
Revealing networks from dynamics: an introduction
What can we learn from the collective dynamics of a complex network about its interaction
topology? Taking the perspective from nonlinear dynamics, we briefly review recent …
topology? Taking the perspective from nonlinear dynamics, we briefly review recent …