Independent Component Analysis
Independent Component Analysis is a statistical method for dimensionality reduction and feature transformation in unsupervised learning that separates a multivariate signal into additive, mutually independent components by maximizing their non-Gaussianity under linear independence constraints.
5.3K
Publications
426.5K
Citations
15.2K
Authors
3.6K
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Publications per year
2017–2026
1.4K
5.3K
Independent component analysis: algorithms and applications
Aapo Hyvärinen, Erkki Oja · Neural Networks · 2000 · 8.8K citations
Independent component analysis, A new concept?
Pierre Comon · Signal Processing · 1994 · 8.2K citations · Full text
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Salk Institute for Biological Studies, United States
52 publications · 32.8K citations
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University of California San Diego
San Diego, United States
70 h-index
428 publications
157.6K citations
University of New Mexico
Albuquerque, United States
55 h-index
311 publications
56K citations
Mind Research Network
Albuquerque, United States
51 h-index
458 publications
84.8K citations
Yale University
New Haven, United States
50 h-index
188 publications
20.2K citations

Centre National de la Recherche Scientifique
Paris, France
45 h-index
263 publications
18.5K citations

Salk Institute for Biological Studies
La Jolla, United States
43 h-index
138 publications
93K citations
University of Oxford
Oxford, United Kingdom
43 h-index
176 publications
54.8K citations
Hartford Financial Services (United States)
Hartford, United States
37 h-index
102 publications
15.1K citations
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168 publications · 24K citations
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137 publications · 15.6K citations
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110 publications · 6.9K citations
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79 publications · 10.4K citations
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77 publications · 6.1K citations
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