Sparse Distributed Representation
Sparse Distributed Representation is a neural coding scheme in which information is represented by the joint activity of a small subset of neurons within a large population, such that each neuron has a specific semantic selectivity and the overall pattern is both sparse in activation and distributed across the network.
64
Publications
5.7K
Citations
150
Authors
91
Institutions
Publications per year
2017–2026
12
Variants
Sdr
Parents
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150
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Institute of Information Technologies and Systems of the National Academy of Sciences of Ukraine, Ukraine
3 publications · 190 citations
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3
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1–5 of 150
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University of California, Berkeley
Berkeley, United States
5 h-index
12 publications
3.2K citations

University of Coimbra
Coimbra, Portugal
3 h-index
8 publications
124 citations

Johns Hopkins University
Baltimore, United States
2 h-index
6 publications
144 citations
V.M. Glushkov Institute of Cybernetics
Kyiv, Ukraine
2 h-index
2 publications
161 citations
Center for the Neural Basis of Cognition
Pittsburgh, United States
2 h-index
4 publications
280 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
2 publications
39 citations
University of California San Diego
San Diego, United States
2 h-index
2 publications
207 citations

University of Toronto
Toronto, Canada
2 h-index
4 publications
1.6K citations
1–8 of 91
Repository · 5 publications · 284 citations
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4 publications · 198 citations
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3 publications · 153 citations
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2 publications · 83 citations
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2 publications · 987 citations
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