Multivariate networks are made up of nodes and their relationships (links), but also data
about those nodes and links as attributes. Most real‐world networks are associated with …

We present a model for building, visualizing, and interacting with multiscale representations
of information visualization techniques using hierarchical aggregation. The motivation for …

可视分析是大数据分析的重要方法. 大数据可视分析旨在利用计算机自动化分析能力的同时,
充分挖掘人对于可视化信息的认知能力优势, 将人, 机的各自强项进行有机融合 …

Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image
classification. With a growing number of classes, the accuracy usually drops as the …

Deep neural networks are now rivaling human accuracy in several pattern recognition
problems. Compared to traditional classifiers, where features are handcrafted, neural …

The analysis of large graphs plays a prominent role in various fields of research and is
relevant in many important application areas. Effective visual analysis of graphs requires …

This survey provides a description of algorithms to reorder visual matrices of tabular data
and adjacency matrix of Networks. The goal of this survey is to provide a comprehensive list …

Data sculptures are an increasingly popular form of physical visualization whose purposes
are essentially artistic, communicative or educational. But can physical visualizations help …

We propose the notion of composite visualization views (CVVs) as a theoretical model that
unifies the existing coordinated multiple views (CMV) paradigm with other strategies for …

The analysis of brain connectivity is a vast field in neuroscience with a frequent use of visual
representations and an increasing need for visual analysis tools. Based on an in-depth …