most citedMachine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide

189 citations · 189 across the 1 of their papers we have counts for

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cond-mat.mtrl-sci2019★ 189 cited

Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide

Ganesh Sivaraman, Anand Narayanan Krishnamoorthy, Matthias Baur +5

We propose a novel active learning scheme for automatically sampling a minimum number of uncorrelated configurations for fitting the Gaussian Approximation Potential (GAP). Our act…