Background The autonomic nervous system (ANS) is a complex network where sympathetic
and parasympathetic domains interact inside and outside of the network. Correlation-based …

In most cases, the official documents related to guidelines and frameworks are complicated,
long, and hard to understand for general readers, regardless of whether the government and …

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 …

We propose an end-to-end architecture for multivariate time-series prediction that integrates
a spatial-temporal graph neural network with a matrix filtering module. This module …

Networks provide useful tools for analysing diverse complex systems from natural, social
and technological domains. Growing size and variety of data such as more nodes and links …

In this work we seek to enhance the frameworks practitioners in asset management and
wealth management may adopt to asses how different screening rules may influence the …

Statistical physics has proved essential to analyze multiagent environments. Motivated by
the empirical observation of various nonequilibrium features in Barro Colorado and other …

We introduce simplicial persistence, a measure of time evolution of motifs in networks
obtained from correlation filtering. We observe long memory in the evolution of structures …