An Information-theoretic Framework for Visualization

By Min Chen, Heike Leitte. 2010

171 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Yingcai Wu
2. Jun Zhu
3. Mengchen Liu
4. Z. Li
5. Jiaxin Shi
6. Anne E. Trefethen
7. Chongxuan Li
8. Shixia Liu

In Computer Vision and Pattern Recognition

1. Jun Zhu
2. Shixia Liu
3. Mengchen Liu
4. Chongxuan Li
5. Yingcai Wu
6. Weiwei Cui
7. Jiaxin Shi
8. Z. Li

Citations in the corpus

• Towards Better Analysis of Deep Convolutional Neural Networks (2016, background): “One way to visualize multiple facets is to overlay one facet on top of another [8, 9].”
• A survey on information visualization: recent advances and challenges (2014, background): “[25,45,158,161] have been proposed to characterize InfoVis from different perspectives such as uncertainty [161] and information theory [25].”
• Visual Multiplexing (2014, methodology): “The most relevant is the information-theoretic framework proposed by Chen and Jänicke [CJ10].”