Random projection forest initialization for graph convolutional networks.

Graph convolutional networks (GCNs) were a great step towards extending deep learning to graphs. GCN uses the graph and the feature matrix as inputs. However, in most cases the graph is missing and we are only provided with the feature matrix .

Automatic transfer function generation using contour tree controlled residue flow model and color harmonics.

Transfer functions facilitate the volumetric data visualization by assigning optical properties to various data features and scalar values. Automation of transfer function specifications still remains a challenge in volume rendering. This paper presents an approach for automating transfer function generations by utilizing topological attributes derived from the contour tree of a volume.

A concept of volume rendering guided search process to analyze medical data set.

This paper firstly presents an approach of parallel coordinates based parameter control panel (PCP). The PCP is used to control parameters of focal region-based volume rendering (FRVR) during data analysis. It uses a parallel coordinates style interface.

Spherical self-organizing map using efficient indexed geodesic data structure.

The two-dimensional (2D) Self-Organizing Map (SOM) has a well-known "border effect". Several spherical SOMs which use lattices of the tessellated icosahedron have been proposed to solve this problem. However, existing data structures for such SOMs are either not space efficient or are time consuming when searching the neighborhood.