We present a system for three-dimensional visualization of complex Liquid Chromatography - Mass Spectrometry (LCMS) data. Every LCMS data point has three attributes: time, mass, a...
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...
In this paper we propose a technique for visualizing steady flow. Using this technique, we first convert the vector field data into a scalar level-set representation. We then a...
A current research topic in molecular thermodynamics is the condensation of vapor to liquid and the investigation of this process at the molecular level. Condensation is found in m...
Sebastian Grottel, Guido Reina, Jadran Vrabec, ...
Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a ...