Massive simulations and arrays of sensing devices, in combination with increasing
computing resources, have generated large, complex, high-dimensional datasets used to …

This paper presents the state of the art in the area of topology‐based visualization. It
describes the process and results of an extensive annotation for generating a definition and …

Multidimensional Projection is a fundamental tool for high-dimensional data analytics and
visualization. With very few exceptions, projection techniques are designed to map data from …

The contour tree is a topological structure associated with a scalar function that tracks the
connectivity of the evolving level sets of the function. It supports intuitive and interactive …

We introduce a new method that identifies and tracks features in arbitrary dimensions using
the merge tree—a structure for identifying topological features based on thresholding in …

High-dimensional data sets commonly occur in various application domains. They are often
analysed using dimensionality reduction methods, such as principal component analysis or …

Sets of multiple scalar fields can be used to model many types of variation in data, such as
uncertainty in measurements and simulations or time‐dependent behavior of scalar …

Creating a static visualization for a time-dependent scalar field is a non-trivial task, yet very
insightful as it shows the dynamics in one picture. Existing approaches are based on a …

The Gaussian mixture model (GMM) describes the distribution of random variables from
several different populations. GMMs have widespread applications in probability theory …

We show how the scalar field topology features of the Topology ToolKit (TTK) can be
leveraged in a pipeline for persistence-based clustering of point clouds. While TTK provides …