Time-series data is widely studied in various scenarios, like weather forecast, stock market,
customer behavior analysis. To comprehensively learn about the dynamic environments, it is …

With the rising necessity of explainable artificial intelligence (XAI), we see an increase in
task-dependent XAI methods on varying abstraction levels. XAI techniques on a global level …

Understanding user behavior patterns and visual analysis strategies is a long-standing
challenge. Existing approaches rely largely on time-consuming manual processes such as …

We present an approach for visual analysis of high-dimensional measurement data with
varying sampling rates in the context of an experimental post-surgery study performed on a …

State-of-the-art game playing programs do not provide an explanation for their move choice
beyond a numerical score for the best and alternative moves. However, human players want …

The increasing size and dimensionality of datasets in the humanities pose new challenges
to scholars working with them, including establishing an overview over the dataset …