Exploring Chemical and Conformational Spaces by Batch Mode Deep Active Learning
Exploring Chemical and Conformational Spaces by Batch Mode Deep Active Learning
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通过批处理模式深度主动学习探索化学和构象空间
DOI:
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发表时间:
2022
期刊:
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通讯作者:
Johannes Kästner
中科院分区:
文献类型:
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作者:
Viktor Zaverkin;David Holzmüller;Ingo Steinwart;Johannes Kästner
The development of machine-learned interatomic potentials requires generating sufficiently expressive atomistic data sets. Active learning algorithms select data points on which labels, i.e., energies and forces, are calculated for inclusion...