Explainable Visual Analytics
Explainable Visual Analytics is a visual analytics approach that integrates transparent, interpretable, and human-understandable mechanisms into the visual data exploration process to make the reasoning, assumptions, and outcomes of analytical models and algorithms comprehensible and justifiable to users.
38
Publications
2.5K
Citations
141
Authors
57
Institutions
Publications per year
2017–2026
27
38
Mastering The Information Age: Solving Problems with Visual Analytics
Jarke J. van Wijk, Tobias Isenberg, Jos B. T. M. Roerdink et al. · 2010 · 424 citations
Visual Analytics for Explainable Deep Learning
Jaegul Choo · IEEE Computer Graphics and Applications · 2018 · 267 citations
Óscar Gómez, Steffen Holter, Jun Yuan et al. · 2020 · 91 citations
1–5 of 38
141
4
h-index
4
h-index
Hong Kong University of Science and Technology, Hong Kong SAR China
3 publications · 76 citations
3
h-index
2
h-index
2
h-index
1–5 of 141
57
Purdue University West Lafayette
West Lafayette, United States
3 h-index
10 publications
200 citations

Zhejiang University
Hangzhou, China
3 h-index
15 publications
877 citations
University of Maryland, College Park
College Park, United States
3 h-index
11 publications
595 citations
University of Konstanz
Konstanz, Germany
3 h-index
12 publications
1.3K citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
3 h-index
8 publications
212 citations
University of Oxford
Oxford, United Kingdom
2 h-index
5 publications
222 citations
New York University
New York, United States
2 h-index
4 publications
322 citations

Pacific Northwest National Laboratory
Richland, United States
2 h-index
4 publications
172 citations
1–8 of 57
TVCG · 11 publications · 674 citations
10
h-index
Repository · 2 publications · 23 citations
2
h-index
3 publications · 312 citations
2
h-index
1 publications · 61 citations
1
h-index
1 publications · 37 citations
1
h-index
1–5