Two-layer Neural Computation
Two-Layer Neural Computation is a computational framework in neuroscience and artificial intelligence that models the integration of synaptic inputs through two hierarchically organized layers of nonlinear processing units, typically representing the interaction between dendritic compartments and somatic output in neurons, thereby enabling enhanced representational capacity beyond single-layer integration.
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703
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316
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2017–2026
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Bidirectional associative memories
Bart Kosko · IEEE Transactions on Systems Man and Cybernetics · 1988 · 2.1K citations
Pyramidal Neuron as Two-Layer Neural Network
Panayiota Poirazi, Terrence Brannon, Bartlett W. Mel · Neuron · 2003 · 822 citations · Full text
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Stanford University
Stanford, United States
12 h-index
23 publications
4.7K citations

Centre National de la Recherche Scientifique
Paris, France
8 h-index
16 publications
736 citations
Massachusetts Institute of Technology
Cambridge, United States
7 h-index
7 publications
132 citations
University of Pittsburgh
Pittsburgh, United States
7 h-index
11 publications
259 citations
Harvard University
Cambridge, United States
6 h-index
9 publications
201 citations

University of Edinburgh
Edinburgh, United Kingdom
6 h-index
9 publications
1K citations
RIKEN Center for Brain Science
Wako, Japan
5 h-index
8 publications
184 citations
Princeton University
Princeton, United States
5 h-index
11 publications
739 citations
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Repository · 43 publications · 2.2K citations
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PRE · 5 publications · 352 citations
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5 publications · 101 citations
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