Neural Representation Learning
Neural Representation Learning is a computational framework within neural encoding that identifies and constructs invariant and meaningful patterns of neural activity to represent sensory, cognitive, or behavioral variables through learned transformations of neural population data.
1.2K
Publications
155.8K
Citations
3.6K
Authors
1K
Institutions
Publications per year
2017–2026
717
Parents
1.2K
Advances in neural information processing systems 7
Krzysztof J. Cios, Mark E. Shields · Neurocomputing · 1997 · 22.3K citations
Advances in neural information processing systems 7
Computers & Mathematics with Applications · 1996 · 14.4K citations
Proceedings of the 21st International Conference on Neural Information Processing Systems
Daphne Koller, Dale Schuurmans, Yoshua Bengio et al. · 2008 · 4.5K citations
1–5 of 1.2K
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McGovern Institute for Brain Research, United States
13 publications · 2.9K citations
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Stanford University
Stanford, United States
26 h-index
89 publications
10.2K citations
Princeton University
Princeton, United States
25 h-index
84 publications
8.8K citations
Carnegie Mellon University
Pittsburgh, United States
24 h-index
75 publications
14.9K citations
University College London
London, United Kingdom
23 h-index
59 publications
12.3K citations
Massachusetts Institute of Technology
Cambridge, United States
22 h-index
74 publications
13.7K citations
Columbia University
New York, United States
20 h-index
53 publications
5.2K citations
University of California San Diego
San Diego, United States
20 h-index
50 publications
11K citations
Harvard University
Cambridge, United States
19 h-index
49 publications
3.4K citations
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Repository · 131 publications · 6K citations
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35 publications · 2.4K citations
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Repository · 63 publications · 2.3K citations
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32 publications · 3K citations
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34 publications · 2.7K citations
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