14 citations · 16 across the 8 of their papers we have counts for
5 papers · 1 filter
Compressed magnetic Moment Tensor Potentials via low-rank matrix and tensor factorizations
Alexey S. Kotykhov, Alexander V. Shapeev, Maxim Rakhuba +1
We propose a parameter-reduced version of magnetic Moment Tensor Potential (mMTP) based on various matrix and tensor decompositions. The resulting compressed magnetic machine-learn…
Automated Prediction of Thermodynamic Properties via Bayesian Free-Energy Reconstruction from Molecular Dynamics
Ekaterina Spirande, Timofei Miryashkin, Andrei Kolmakov +1
Accurate free-energy calculations are essential for predicting thermodynamic properties and phase stability, but existing methods are limited: phonon-based approaches neglect anhar…
Accelerating Structure Prediction of Molecular Crystals using Actively Trained Moment Tensor Potential
Nikita Rybin, Ivan S. Novikov, Alexander Shapeev
Inspired by the recent success of machine-learned interatomic potentials for crystal structure prediction of the inorganic crystals, we present a methodology that exploits Moment T…
A moment tensor potential for lattice thermal conductivity calculations of alpha and beta phases of Ga2O3
Nikita Rybin, Alexander Shapeev
Calculations of heat transport in crystalline materials have recently become mainstream, thanks to machine-learned interatomic potentials that allow for significant computational c…
Automated optimization of convergence parameters in plane wave density functional theory calculations via a tensor decomposition-based uncertainty quantification
Jan Janssen, Edgar Makarov, Tilmann Hickel +2
First principles approaches have revolutionized our ability in using computers to predict, explore and design materials. A major advantage commonly associated with these approaches…