In situ visualization is clearly a promising solution for ultrascale simulations. We've seen
some success in realizing this solution and in ongoing efforts to add support for in situ …

The most common abstraction used by visualization libraries and applications today is what
is known as the visualization pipeline. The visualization pipeline provides a mechanism to …

We present TSR-TVD, a novel deep learning framework that generates temporal super-
resolution (TSR) of time-varying data (TVD) using adversarial learning. TSR-TVD is the first …

We present a new algorithm to explore and visualize multivariate time-varying data sets. We
identify important trend relationships among the variables based on how the values of the …

Weather conditions affect multiple aspects of human life such as economy, safety, security,
and social activities. For this reason, weather forecast plays a major role in society. Currently …

Effective analysis and visualization of time-varying multivariate data is crucial for
understanding complex and dynamic variable interaction and temporal evolution. Advances …

We present a correlation study of time-varying multivariate volumetric data sets. In most
scientific disciplines, to test hypotheses and discover insights, scientists are interested in …

Finding correlations among data is one of the most essential tasks in many scientific
investigations and discoveries. This paper addresses the issue of creating a static volume …

Studying the dynamic evolution of time-varying volumetric data is essential in countless
scientific endeavors. The ability to isolate and track features of interest allows domain …

Driven by the ability to generate ever-larger, increasingly complex data, there is an urgent
need in the scientific community for scalable analysis methods that can rapidly identify …