Multivariate networks are made up of nodes and their relationships (links), but also data
about those nodes and links as attributes. Most real‐world networks are associated with …

Whether AI explanations can help users achieve specific tasks efficiently (ie, usable
explanations) is significantly influenced by their visual presentation. While many techniques …

Convolutional neural networks are at the core of state-of-the-art approaches to a variety of
computer vision tasks. Visualizations of neural networks typically take the form of static …

Visualization researchers and practitioners engaged in generating or evaluating designs are
faced with the difficult problem of transforming the questions asked and actions taken by …

The increasing reliance on Large Language Models (LLMs) for health information seeking
can pose severe risks due to the potential for misinformation and the complexity of these …

Pathway analysis is a powerful method for data analysis in genomics, most often applied to
gene expression analysis. It is also promising for single-nucleotide polymorphism (SNP) …

Making sense of large graph datasets is a fundamental and challenging process that
advances science, education and technology. We survey research on graph exploration and …

Current mobile devices are often equipped with several network interfaces, which may be of
different access technologies, both wireless and cellular. Different requirements of different …

We present NeuroLines, a novel visualization technique designed for scalable detailed
analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue …

We extend the popular brushing and linking technique by incorporating personal agency in
the interaction. We map existing research related to brushing and linking into a design …