Visualization and visual analysis play important roles in exploring, analyzing, and
presenting scientific data. In many disciplines, data and model scenarios are becoming …

Most visualization techniques have been designed on the assumption that the data to be
represented are free from uncertainty. Yet this is rarely the case. Recently the visualization …

Over the last decade, ensemble visualization has witnessed a significant development due
to the wide availability of ensemble data, and the increasing visualization needs from a …

The goal of visualization is to effectively and accurately communicate data. Visualization
research has often overlooked the errors and uncertainty which accompany the scientific …

Various case studies in different application domains have shown the great potential of
visual parameter space analysis to support validating and using simulation models. In order …

With data comes uncertainty, which is a widespread and frequent phenomenon in data
science and analysis. The amount of information available to us is growing exponentially …

We propose InSituNet, a deep learning based surrogate model to support parameter space
exploration for ensemble simulations that are visualized in situ. In situ visualization …

Numerical weather prediction ensembles are routinely used for operational weather
forecasting. The members of these ensembles are individual simulations with either slightly …

Visualization of climate data plays an integral role in the communication of climate change
findings to both expert and non-expert audiences. The cognitive and psychological sciences …

Ensembles of numerical simulations are used in a variety of applications, such as
meteorology or computational solid mechanics, in order to quantify the uncertainty or …