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A scalable implementation of the recursive least-squares algorithm for training spiking neural networks
Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a popular way to study computations performed by the nervous system. As the size and complexity of neural recordings increase, there is a need for efficient algorithms that can train models in a short pe...
| 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/PMC10333503/ https://www.ncbi.nlm.nih.gov/pubmed/37441157 http://dx.doi.org/10.3389/fninf.2023.1099510 |