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We report a new deep learning message passing network that takes inspiration from Newton's equations of motion to learn interatomic potentials and forces.
Density-Functional Theory of Atoms and Molecules
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Generalized neural-network representation of high-dimensional potential-energy surfaces
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2015
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Ani-1: an extensible neural network potential with dft accuracy at force field computational cost
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Stefan Chmiela, Alexandre Tkatchenko, Huziel E Sauceda, Igor Poltavsky, Kristof T Schütt, Klaus-robert Müller, Igor Poltavsky, and Kristof T Sch · 2017
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Directional Message Passing for Molecular Graphs
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Incompleteness of atomic structure representations
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Benchmarking the Performance of the ReaxFF Reactive Force Field on Hydrogen Combustion Systems
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