no code implementations • 25 Oct 2021 • Xiwei Xuan, XiaoYu Zhang, Oh-Hyun Kwon, Kwan-Liu Ma
The rapid development of Convolutional Neural Networks (CNNs) in recent years has triggered significant breakthroughs in many machine learning (ML) applications.
no code implementations • 11 Oct 2021 • Oh-Hyun Kwon, Chiun-How Kao, Chun-houh Chen, Kwan-Liu Ma
Depending on the node ordering, an adjacency matrix can highlight distinct characteristics of a graph.
no code implementations • 10 May 2019 • Takanori Fujiwara, Oh-Hyun Kwon, Kwan-Liu Ma
Dimensionality reduction (DR) is frequently used for analyzing and visualizing high-dimensional data as it provides a good first glance of the data.
1 code implementation • 27 Apr 2019 • Oh-Hyun Kwon, Kwan-Liu Ma
To provide users with an intuitive way to navigate the layout design space, we present a technique to systematically visualize a graph in diverse layouts using deep generative models.
no code implementations • 11 Oct 2017 • Oh-Hyun Kwon, Tarik Crnovrsanin, Kwan-Liu Ma
For a given graph, our approach can show what the graph would look like in different layouts and estimate their corresponding aesthetic metrics.