For decades, researchers in information visualisation and graph drawing have focused on
developing techniques for the layout and display of very large and complex networks …

Visualizing network data is applicable in domains such as biology, engineering, and social
sciences. We report the results of a study comparing the effectiveness of the two primary …

Constructing latent vector representation for nodes in a network through embedding models
has shown its practicality in many graph analysis applications, such as node classification …

Understanding team communication and collaboration patterns is critical for improving work
efficiency in organizations. This paper presents an interactive visualization system, T-Cal …

Abstract Analysis of functional magnetic resonance imaging (fMRI) plays a pivotal role in
uncovering an understanding of the brain. fMRI data contain both spatial volume and …

We introduce NeuroCave, a novel immersive visualization system that facilitates the visual
inspection of structural and functional connectome datasets. The representation of the …

Visualizing network data is applicable in domains such as biology, engineering, and social
sciences. We report the results of a study comparing the effectiveness of the two primary …

An electroencephalography (EEG) coherence network is a representation of functional brain
connectivity, and is constructed by calculating the coherence between pairs of electrode …

We address the problem of exploring, combining, and comparing large collections of scored,
directed networks for understanding inferred Bayesian networks used in biology. In this field …

Brain science, as an important branch of Neuroscience, is a discipline that studies the
structure and function of brain nervous system of human and other mammals. With the …