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Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models
Understanding neural computation on the mechanistic level requires models of neurons and neuronal networks. To analyze such models one typically has to solve coupled ordinary differential equations (ODEs), which describe the dynamics of the underlying neural system. These ODEs are solved numerically...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9666333/ https://www.ncbi.nlm.nih.gov/pubmed/35932442 http://dx.doi.org/10.1007/s10827-022-00827-7 |