Recent advances in imaging and tracing technology provide increasingly detailed
reconstructions of brain connectomes. Concomitant analytic advances enable rigorous …

The number of network science applications across many different fields has been rapidly
increasing. Surprisingly, the development of theory and domain-specific applications often …

This paper studies the risk diffusion in the cryptocurrency market during the period from
2018 to 2021 based on the network analysis. By comparing the network topologies of …

Functional connectivity is derived from inter-regional correlations in spontaneous
fluctuations of brain activity, and can be represented in terms of complete graphs with …

This paper studies the risk spreading ability of cryptocurrencies and their contribution to the
systemic risk during the period from 2018 to 2022. Three different network centrality …

With the recent availability of tissue-specific gene expression data, eg, provided by the GTEx
Consortium, there is interest in comparing gene co-expression patterns across tissues. One …

Uncertain networks, ie, graphs where each edge is associated with a probability of
existence, have received a great deal of attention thanks to their expressivity and …

Many empirical networks originate from correlational data, arising in domains as diverse as
psychology, neuroscience, genomics, microbiology, finance, and climate science …

A dynamic factor model with a mixture distribution of the loadings is introduced and studied
for multivariate, possibly high-dimensional time series. The correlation matrix of the model …

Network analysis has been applied to various correlation matrix data. Thresholding on the
value of the pairwise correlation is probably the most straightforward and common method to …