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Machine Learning for Absorption Cross Sections
[Image: see text] We present a machine learning (ML) method to accelerate the nuclear ensemble approach (NEA) for computing absorption cross sections. ML-NEA is used to calculate cross sections on vast ensembles of nuclear geometries to reduce the error due to insufficient statistical sampling. The...
Gorde:
| Argitaratua izan da: | J Phys Chem A |
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| Egile Nagusiak: | , , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
American Chemical
Society
2020
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| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7511037/ https://ncbi.nlm.nih.gov/pubmed/32786977 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1021/acs.jpca.0c05310 |
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