Published in
Royal Society of Chemistry, Chemical Science, 34(10), p. 7913-7922, 2019
DOI: 10.1039/c9sc02298h
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A quantitative uncertainty metric controls error in neural network-driven chemical discovery
Journal article published in 2019 by
Jon Paul Janet 
,
Chenru Duan ,
Tzuhsiung Yang,
Aditya Nandy ,
Heather J. Kulik
,
Chenru Duan ,
Tzuhsiung Yang,
Aditya Nandy ,
Heather J. Kulik
This paper is made freely available by the publisher.
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Abstract
A predictive approach for driving down machine learning model errors is introduced and demonstrated across discovery for inorganic and organic chemistry.