Cargando…
A Bayesian graph convolutional network for reliable prediction of molecular properties with uncertainty quantification
Deep neural networks have been increasingly used in various chemical fields. In the nature of a data-driven approach, their performance strongly depends on data used in training. Therefore, models developed in data-deficient situations can cause highly uncertain predictions, leading to vulnerable de...
| Autores principales: | , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Royal Society of Chemistry
2019
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6839511/ https://www.ncbi.nlm.nih.gov/pubmed/31803423 http://dx.doi.org/10.1039/c9sc01992h |