Brain-Inspired Hardware Solutions for Inference in Bayesian Networks
The implementation of inference (i.e., computing posterior probabilities) in Bayesian networks using a conventional computing paradigm turns out to be inefficient in terms of energy, time, and space, due to the substantial resources required by floating-point operations. A departure from conventiona...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8677599/ https://www.ncbi.nlm.nih.gov/pubmed/34924925 http://dx.doi.org/10.3389/fnins.2021.728086 |