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A hybrid framework for improving uncertainty quantification in deep learning-based QSAR regression modeling
Reliable uncertainty quantification for statistical models is crucial in various downstream applications, especially for drug design and discovery where mistakes may incur a large amount of cost. This topic has therefore absorbed much attention and a plethora of methods have been proposed over the p...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8454160/ https://www.ncbi.nlm.nih.gov/pubmed/34544485 http://dx.doi.org/10.1186/s13321-021-00551-x |