Machine learning for molecular and materials science
Top Cited Papers
- 25 July 2018
- journal article
- review article
- Published by Springer Science and Business Media LLC in Nature
- Vol. 559 (7715), 547-555
- https://doi.org/10.1038/s41586-018-0337-2
Abstract
Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence.This publication has 85 references indexed in Scilit:
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