Latent Space Interpretation
Latent Space Interpretation is a computational framework in multi-omics analysis that identifies and characterizes biologically meaningful representations by decoding abstract, reduced-dimensional embeddings derived from heterogeneous omics data.
546
Publications
34.3K
Citations
2K
Authors
617
Institutions
Publications per year
2017–2026
455
Parents
546
Reading Tea Leaves: How Humans Interpret Topic Models
Jonathan Chang, Sean Gerrish, Chong Wang et al. · 2009 · 1.9K citations
Interpreting the Latent Space of GANs for Semantic Face Editing
Yujun Shen, Jinjin Gu, Xiaoou Tang et al. · 2020 · 1K citations
SPECTRAL CLUSTERING AND THE HIGH-DIMENSIONAL STOCHASTIC BLOCKMODEL
Karl Rohe, Sourav Chatterjee, Bin Yu · 2013 · 799 citations
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617
University of Washington
Seattle, United States
15 h-index
49 publications
4.5K citations
Carnegie Mellon University
Pittsburgh, United States
11 h-index
19 publications
1.3K citations
Tsinghua University
Beijing, China
10 h-index
25 publications
1.8K citations

Centre National de la Recherche Scientifique
Paris, France
9 h-index
28 publications
1K citations

Zhejiang University
Hangzhou, China
9 h-index
23 publications
701 citations
Tencent (China)
Shenzhen, China
9 h-index
17 publications
686 citations
University of Oxford
Oxford, United Kingdom
8 h-index
30 publications
1.5K citations
Duke University
Durham, United States
8 h-index
20 publications
2.9K citations
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Repository · 68 publications · 3.5K citations
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Repository · 11 publications · 488 citations
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TOG · 14 publications · 1.7K citations
13
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12 publications · 764 citations
12
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Conference · 9 publications · 1K citations
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