Visualizations are now widely used across disciplines to understand and communicate data.
The benefit of visualizations lies in leveraging our natural visual perception. However, the …

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 …

Learn How to Design Effective Visualization SystemsVisualization Analysis and Design
provides a systematic, comprehensive framework for thinking about visualization in terms of …

Deep learning is increasingly used in decision-making tasks. However, understanding how
neural networks produce final predictions remains a fundamental challenge. Existing work …

The increasing scale and availability of digital data provides an extraordinary resource for
informing public policy, scientific discovery, business strategy, and even our personal lives …

The analysis of large graphs plays a prominent role in various fields of research and is
relevant in many important application areas. Effective visual analysis of graphs requires …

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 …

Data visualization systems have predominantly been developed for WIMP-based direct
manipulation interfaces. Only recently have other forms of interaction begun to appear, such …

We present PivotPaths, an interactive visualization for exploring faceted information
resources. During both work and leisure, we increasingly interact with information spaces …

Network data is ubiquitous; e-mail traffic between persons, telecommunication, transport and
financial networks are some examples. Often these networks are large and multivariate …