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Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures
Spiking Neural Networks (SNNs) have recently emerged as a prominent neural computing paradigm. However, the typical shallow SNN architectures have limited capacity for expressing complex representations while training deep SNNs using input spikes has not been successful so far. Diverse methods have...
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| Publicado no: | Front Neurosci |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7059737/ https://ncbi.nlm.nih.gov/pubmed/32180697 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2020.00119 |
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