100 citations · 592 across the 42 of their papers we have counts for
42 papers
Character-Oriented Design for Visual Data Storytelling
Keshav Dasu, Yun-Hsin Kuo, Kwan-Liu Ma
When telling a data story, an author has an intention they seek to convey to an audience. This intention can be of many forms such as to persuade, to educate, to inform, or even to…
Feature Learning for Nonlinear Dimensionality Reduction toward Maximal Extraction of Hidden Patterns
Takanori Fujiwara, Yun-Hsin Kuo, Anders Ynnerman +1
Dimensionality reduction (DR) plays a vital role in the visual analysis of high-dimensional data. One main aim of DR is to reveal hidden patterns that lie on intrinsic low-dimensio…
A Machine-Learning-Aided Visual Analysis Workflow for Investigating Air Pollution Data
Yun-Hsin Kuo, Takanori Fujiwara, Charles C. -K. Chou +2
Analyzing air pollution data is challenging as there are various analysis focuses from different aspects: feature (what), space (where), and time (when). As in most geospatial anal…
A Deep Generative Model for Reordering Adjacency Matrices
Oh-Hyun Kwon, Chiun-How Kao, Chun-houh Chen +1
Depending on the node ordering, an adjacency matrix can highlight distinct characteristics of a graph. Deriving a "proper" node ordering is thus a critical step in visualizing a gr…
A Visual Analytics System for Water Distribution System Optimization
Yiran Li, Erin Musabandesu, Takanori Fujiwara +2
The optimization of water distribution systems (WDSs) is vital to minimize energy costs required for their operations. A principal approach taken by researchers is identifying an o…
Interactive Dimensionality Reduction for Comparative Analysis
Takanori Fujiwara, Xinhai Wei, Jian Zhao +1
Finding the similarities and differences between groups of datasets is a fundamental analysis task. For high-dimensional data, dimensionality reduction (DR) methods are often used…