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From statistical inference to a differential learning rule for stochastic neural networks
Stochastic neural networks are a prototypical computational device able to build a probabilistic representation of an ensemble of external stimuli. Building on the relationship between inference and learning, we derive a synaptic plasticity rule that relies only on delayed activity correlations, and...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6227809/ https://www.ncbi.nlm.nih.gov/pubmed/30443331 http://dx.doi.org/10.1098/rsfs.2018.0033 |