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Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials

Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials

Viktor Zaverkin
Johannes Kastner
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Papers citing "Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials"

2 / 2 papers shown
Title
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials
Matthias Holzenkamp
Dongyu Lyu
Ulrich Kleinekathöfer
Peter Zaspel
46
0
0
10 Jan 2025
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
M. Rupp
A. Tkatchenko
K. Müller
O. A. von Lilienfeld
AI4CE
44
1,581
0
12 Sep 2011

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