Learning a Local-Variable Model of Aromatic and Conjugated Systems
A collection of new approaches to building and training neural networks, collectively referred to as deep learning, are attracting attention in theoretical chemistry. Several groups aim to replace computationally expensive ab initio quantum mechanics calculations with learned estimators. This raises...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Chemical Society
2018-01-01
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| Series: | ACS Central Science |
| Online Access: | http://dx.doi.org/10.1021/acscentsci.7b00405 |