Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning

26 March 2020

Papers citing "Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning"

4 / 4 papers shown

Title
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials Matthias Holzenkamp Dongyu Lyu Ulrich Kleinekathöfer Peter Zaspel 33 0 0 10 Jan 2025
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials Viktor Zaverkin Johannes Kastner 34 67 0 15 Sep 2021
A Universal Framework for Featurization of Atomistic Systems Xiangyun Lei A. Medford AI4CE 18 19 0 04 Feb 2021
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 149 446 0 16 Sep 2019