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Predictive learning as a network mechanism for extracting low-dimensional latent space representations
Artificial neural networks have recently achieved many successes in solving sequential processing and planning tasks. Their success is often ascribed to the emergence of the task’s low-dimensional latent structure in the network activity – i.e., in the learned neural representations. Here, we invest...
Autores principales: | Recanatesi, Stefano, Farrell, Matthew, Lajoie, Guillaume, Deneve, Sophie, Rigotti, Mattia, Shea-Brown, Eric |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930246/ https://www.ncbi.nlm.nih.gov/pubmed/33658520 http://dx.doi.org/10.1038/s41467-021-21696-1 |
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