Autoencoder-based Fusion
Autoencoder-Based Fusion is a data integration framework that employs autoencoder architectures to jointly learn compressed, latent representations from multiple omics data types by leveraging their shared underlying biological structure to enable downstream multi-omics analysis.
91
Publications
4.3K
Citations
330
Authors
173
Institutions
Publications per year
2017–2026
89
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91
1–5 of 91
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173

Cochin University of Science and Technology
Ernakulam, India
4 h-index
6 publications
315 citations

Beihang University
Beijing, China
4 h-index
15 publications
265 citations

Shenzhen University
Shenzhen, China
3 h-index
2 publications
48 citations
Tsinghua University
Beijing, China
3 h-index
7 publications
240 citations

Northwestern Polytechnical University
Xi'an, China
3 h-index
5 publications
238 citations
Nanjing University
Nanjing, China
2 h-index
2 publications
24 citations

Zhejiang University
Hangzhou, China
2 h-index
6 publications
252 citations

Capital Medical University
Beijing, China
2 h-index
5 publications
933 citations
1–8 of 173
4 publications · 392 citations
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2 publications · 308 citations
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3 publications · 125 citations
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3 publications · 88 citations
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3 publications · 112 citations
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