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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...
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| Foilsithe in: | Interface Focus |
|---|---|
| Main Authors: | , , , , |
| Formáid: | Artigo |
| Teanga: | Inglês |
| Foilsithe: |
The Royal Society
2018
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| Ábhair: | |
| Rochtain Ar Líne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6227809/ https://ncbi.nlm.nih.gov/pubmed/30443331 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1098/rsfs.2018.0033 |
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