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Tsz Wai Ko

Showing results (1-10 of 9) with videos related to

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Nature Computational Science|January 4, 2024
Recent advances and outstanding challenges for machine learning interatomic potentialsTsz Wai Ko, Shyue Ping Ong
Annual Review of Physical Chemistry|January 4, 2022
Neural Network Potentials: A Concise Overview of MethodsEmir Kocer, Tsz Wai Ko, Jörg Behler
Journal of Chemical Theory and Computation|June 8, 2023
Accurate Fourth-Generation Machine Learning Potentials by Electrostatic EmbeddingTsz Wai Ko, Jonas A Finkler, Stefan Goedecker, et al.
Accounts of Chemical Research|January 29, 2021
General-Purpose Machine Learning Potentials Capturing Nonlocal Charge TransferTsz Wai Ko, Jonas A Finkler, Stefan Goedecker, et al.
Nature Communications|January 16, 2021
A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transferTsz Wai Ko, Jonas A Finkler, Stefan Goedecker, et al.
The Journal of Chemical Physics|March 25, 2025
Iterative charge equilibration for fourth-generation high-dimensional neural network potentialsEmir Kocer, Andreas Singraber, Jonas A Finkler, et al.
Nano Letters|August 15, 2025
Superionic Surface Li-Ion Transport in Carbonaceous MaterialsJianbin Zhou, Shen Wang, Chaoshan Wu, et al.
Chemical Science|February 6, 2025
Crash testing machine learning force fields for molecules, materials, and interfaces: molecular dynamics in the TEA challenge 2023Igor Poltavsky, Mirela Puleva, Anton Charkin-Gorbulin, et al.
Chemical Science|February 12, 2025
Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023Igor Poltavsky, Anton Charkin-Gorbulin, Mirela Puleva, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Nature Computational Science|January 4, 2024
Recent advances and outstanding challenges for machine learning interatomic potentialsTsz Wai Ko, Shyue Ping Ong
Annual Review of Physical Chemistry|January 4, 2022
Neural Network Potentials: A Concise Overview of MethodsEmir Kocer, Tsz Wai Ko, Jörg Behler
Journal of Chemical Theory and Computation|June 8, 2023
Accurate Fourth-Generation Machine Learning Potentials by Electrostatic EmbeddingTsz Wai Ko, Jonas A Finkler, Stefan Goedecker, et al.
Accounts of Chemical Research|January 29, 2021
General-Purpose Machine Learning Potentials Capturing Nonlocal Charge TransferTsz Wai Ko, Jonas A Finkler, Stefan Goedecker, et al.
Nature Communications|January 16, 2021
A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transferTsz Wai Ko, Jonas A Finkler, Stefan Goedecker, et al.
The Journal of Chemical Physics|March 25, 2025
Iterative charge equilibration for fourth-generation high-dimensional neural network potentialsEmir Kocer, Andreas Singraber, Jonas A Finkler, et al.
Nano Letters|August 15, 2025
Superionic Surface Li-Ion Transport in Carbonaceous MaterialsJianbin Zhou, Shen Wang, Chaoshan Wu, et al.
Chemical Science|February 6, 2025
Crash testing machine learning force fields for molecules, materials, and interfaces: molecular dynamics in the TEA challenge 2023Igor Poltavsky, Mirela Puleva, Anton Charkin-Gorbulin, et al.
Chemical Science|February 12, 2025
Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023Igor Poltavsky, Anton Charkin-Gorbulin, Mirela Puleva, et al.
Pageof 1