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research article
Quantum Chemistry Meets Machine Learning
December 1, 2019
In this account, we demonstrate how statistical learning approaches can be leveraged across a range of different quantum chemical areas to transform the scaling, nature, and complexity of the problems that we are tackling. Selected examples illustrate the power brought by kernel-based approaches in the large-scale screening of homogeneous catalysis, the prediction of fundamental quantum chemical properties and the free-energy landscapes of flexible organic molecules. While certainly non-exhaustive, these examples provide an intriguing glimpse into our own research efforts.
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Type
research article
Web of Science ID
WOS:000504762100003
Authors
Publication date
2019-12-01
Publisher
Published in
Volume
73
Issue
12
Start page
983
End page
989
Peer reviewed
REVIEWED
EPFL units
Available on Infoscience
January 15, 2020