Nonlinear reconfiguration of network edges, topology and information content during an artificial learning task
Abstract Here, we combine network neuroscience and machine learning to reveal connections between the brain’s network structure and the emerging network structure of an artificial neural network. Specifically, we train a shallow, feedforward neural network to classify hand-written digits and then us...
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Autores principales: | , , , , |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
SpringerOpen
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/56535ee1d8f24f75addbbf7d10541b34 |
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