Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
We present a practical and general-purpose approach to large and complex visual data analysis where visualization processing, rendering and subsequent human interpretation is cons...
Kurt Stockinger, John Shalf, Kesheng Wu, E. Wes Be...
Single-particle 3D reconstruction from cryo-electron microscopy (cryo-EM) images is a kernel application of biological molecules analysis, as the computational requirement of whic...
Graphs are well-known, well-understood, and frequently used means to depict networks of related items. They are successfully used as the underlying mathematical concept in various ...
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...