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Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines
An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and l...
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| Publicado no: | Front Neurosci |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5478701/ https://ncbi.nlm.nih.gov/pubmed/28680387 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2017.00324 |
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