Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

Knowledge of human perception has long been incorporated into visualizations to enhance
their quality and effectiveness. The last decade, in particular, has shown an increase in …

t-Distributed Stochastic Neighbor Embedding (t-SNE) for the visualization of
multidimensional data has proven to be a popular approach, with successful applications in …

Inspired by the great success of machine learning (ML), researchers have applied ML
techniques to visualizations to achieve a better design, development, and evaluation of …

Visualization and artificial intelligence (AI) are well-applied approaches to data analysis. On
one hand, visualization can facilitate humans in data understanding through intuitive visual …

Dimensionality Reduction (DR) techniques can generate 2D projections and enable visual
exploration of cluster structures of high-dimensional datasets. However, different DR …

Despite the rising popularity of automated visualization tools, existing systems tend to
provide direct results which do not always fit the input data or meet visualization …

COVID-19 is a rapidly spreading viral disease and has affected over 100 countries
worldwide. The numbers of casualties and cases of infection have escalated particularly in …

Visual clustering is a common perceptual task in scatterplots that supports diverse analytics
tasks (eg, cluster identification). However, even with the same scatterplot, the ways of …

Scatterplots are among the most widely used visualization techniques. Compelling
scatterplot visualizations improve understanding of data by leveraging visual perception to …