Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide

HIGHLIGHTS

• who: Ganesh Sivaraman from the (UNIVERSITY) have published the Article: Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide, in the Journal: (JOURNAL) of 22/06/2020
• what: Within the context of this article, the goal is to devise an active learner that can automatically select a minimum number of training configurations that would result in a near DFT accuracy ML interatomic potential. Inspired by the original work of Dasgupta et_al21, the authors propose an active learner which aims to exploit the cluster structure embedded in a given unlabeled dataset so as . . .
  

   

  

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