224 citations · 654 across the 20 of their papers we have counts for
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MLIP-3: Active learning on atomic environments with Moment Tensor Potentials
Evgeny Podryabinkin, Kamil Garifullin, Alexander Shapeev +1
Nowadays, academic research relies not only on sharing with the academic community the scientific results obtained by research groups while studying certain phenomena, but also on…
The MLIP package: Moment Tensor Potentials with MPI and Active Learning
Ivan S. Novikov, Konstantin Gubaev, Evgeny V. Podryabinkin +1
The subject of this paper is the technology (the "how") of constructing machine-learning interatomic potentials, rather than science (the "what" and "why") of atomistic simulations…
Improving accuracy of interatomic potentials: more physics or more data? A case study of silica
Ivan S. Novikov, Alexander V. Shapeev
In this paper we test two strategies to improving the accuracy of machine-learning potentials, namely adding more fitting parameters thus making use of large volumes of available q…