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 …

We present and evaluate an implementation technique for histogram-like computations on
GPUs that ensures both work-efficient asymptotic cost, support for arbitrary associative and …

Although supercomputers are becoming increasingly powerful, their components have thus
far not scaled proportionately. Compute power is growing enormously and is enabling finely …

We propose a data reduction technique for scattered data based on statistical sampling. Our
void-and-cluster sampling technique finds a representative subset that is optimally …

The past decade has witnessed the superior power of deep neural networks (DNNs) in
applications across various domains. However, training a high-quality DNN remains a non …

Creating a data representation is a common approach for efficient and effective data
management and exploration. The compressed bitmap indexing is one of the emerging data …

CoDDA (C opula-based D istribution D riven A nalysis) is a flexible framework for large-
scale multivariate datasets. A common strategy to deal with large-scale scientific simulation …

With increasing computing capabilities of modern supercomputers, the size of the data
generated from the scientific simulations is growing rapidly. As a result, application scientists …

Analyzing scientific datasets created from simulations on modern supercomputers is a
daunting challenge due to the fast pace at which these datasets continue to grow. Low cost …

For an ensemble of 3D multi-parameter fields, we present a visual analytics workflow to
analyse whether and which parts of a selected multi-parameter distribution is present in all …