Currently, growing data sources and long-running algorithms impede user attention and
interaction with visual analytics applications. Progressive visualization (PV) and visual …

We present a machine learning-based approach for detecting and visualizing complex
behavior in spatiotemporal volumes. For this, we train models to predict future data values at …

We present a Cerebral Aneurysm Vortex Classification (CAVOCLA) that allows to classify
blood flow in cerebral aneurysms. Medical studies assume a strong relation between the …

Recent advances in high-resolution microscopy have allowed scientists to better understand
the underlying brain connectivity. However, due to the limitation that biological specimens …

We study the question of how visual analysis can support the comparison of spatio-temporal
ensemble data of liquid and gas flow in porous media. To this end, we focus on a case …

Effective exploration of spatiotemporal volumetric data sets remains a key challenge in
scientific visualization. Although great advances have been made over the years, existing …

Increasingly fast computing systems for simulations and high-accuracy measurement
techniques drive the generation of time-dependent volumetric data sets with high resolution …

Progressive visualization allows users to examine intermediate results while they are further
refined in the background. This makes them increasingly popular when dealing with large …

We present a GPU-targeted algorithm for the efficient direct computation of distances and
interpolates between high-resolution density distributions without requiring any kind of …

We visualize contours for spatio‐temporal processes to indicate where and when non‐
continuous changes occur or spatial bounds are encountered. All time steps are comprised …