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Neural Stochastic Differential Equations with Neural Processes Family Members for Uncertainty Estimation in Deep Learning
Existing neural stochastic differential equation models, such as SDE-Net, can quantify the uncertainties of deep neural networks (DNNs) from a dynamical system perspective. SDE-Net is either dominated by its drift net with in-distribution (ID) data to achieve good predictive accuracy, or dominated b...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197858/ https://www.ncbi.nlm.nih.gov/pubmed/34073566 http://dx.doi.org/10.3390/s21113708 |