Labels
Labels is a visual annotation technique that belongs to the class of textual aids in visualization, differentiating itself by explicitly identifying specific data elements, features, or regions within a visual representation to enhance interpretability and direct viewer attention.
8.4K
Publications
644.3K
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24.7K
Authors
4.4K
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Publications per year
2017–2026
4.2K
Parents
8.4K
UMAP: Uniform Manifold Approximation and Projection
Leland McInnes, John Healy, Nathaniel Saul et al. · The Journal of Open Source Software · 2018 · 9.6K citations · Full text
KEGG: new perspectives on genomes, pathways, diseases and drugs
Minoru Kanehisa, Miho Furumichi, Mao Tanabe et al. · Nucleic Acids Research · 2016 · 9.4K citations · Full text
Conditional Generative Adversarial Nets
Mehdi Mirza, Simon Osindero · arXiv (Cornell University) · 2014 · 8.9K citations · Full text
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Carnegie Mellon University
Pittsburgh, United States
67 h-index
346 publications
86.9K citations
Stanford University
Stanford, United States
63 h-index
391 publications
99.8K citations

Chinese Academy of Sciences
Beijing, China
54 h-index
388 publications
30.6K citations
Google (United States)
Mountain View, United States
51 h-index
330 publications
126.2K citations
Tsinghua University
Beijing, China
45 h-index
329 publications
16K citations
University of Oxford
Oxford, United Kingdom
44 h-index
182 publications
17.7K citations
Nanjing University
Nanjing, China
43 h-index
208 publications
20.7K citations
Microsoft (United States)
Redmond, United States
43 h-index
213 publications
19.1K citations
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Repository · 642 publications · 56.9K citations
89
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Conference · 166 publications · 12.7K citations
55
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TPAMI · 100 publications · 18.8K citations
52
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77 publications · 6.6K citations
43
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Conference · 53 publications · 4.4K citations
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