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Gradient-based feature-attribution explainability methods for spiking neural networks
INTRODUCTION: Spiking neural networks (SNNs) are a model of computation that mimics the behavior of biological neurons. SNNs process event data (spikes) and operate more sparsely than artificial neural networks (ANNs), resulting in ultra-low latency and small power consumption. This paper aims to ad...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10565802/ https://www.ncbi.nlm.nih.gov/pubmed/37829721 http://dx.doi.org/10.3389/fnins.2023.1153999 |