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Albert Musaelian

Showing results (1-10 of 8) with videos related to

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The Journal of Chemical Physics|April 27, 2023
Fast uncertainty estimates in deep learning interatomic potentialsAlbert Zhu, Simon Batzner, Albert Musaelian, et al.
Nature Communications|February 3, 2023
Learning local equivariant representations for large-scale atomistic dynamicsAlbert Musaelian, Simon Batzner, Anders Johansson, et al.
ACS Omega|March 11, 2024
Accurate Surface and Finite-Temperature Bulk Properties of Lithium Metal at Large Scales Using Machine Learning Interaction PotentialsMgcini Keith Phuthi, Archie Mingze Yao, Simon Batzner, et al.
Nature Communications|April 29, 2025
Unified differentiable learning of electric responseStefano Falletta, Andrea Cepellotti, Anders Johansson, et al.
Nature Communications|May 4, 2022
E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentialsSimon Batzner, Albert Musaelian, Lixin Sun, et al.
Nature Machine Intelligence|January 29, 2025
The design space of E(3)-equivariant atom-centred interatomic potentialsIlyes Batatia, Simon Batzner, Dávid Péter Kovács, et al.
The Journal of Physical Chemistry Letters|July 18, 2024
Transferability and Accuracy of Ionic Liquid Simulations with Equivariant Machine Learning Interatomic PotentialsZachary A H Goodwin, Malia B Wenny, Julia H Yang, et al.
Journal of the American Chemical Society|August 15, 2020
Evolution of Metastable Structures at Bimetallic Surfaces from Microscopy and Machine-Learning Molecular DynamicsJin Soo Lim, Jonathan Vandermause, Matthijs A van Spronsen, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
The Journal of Chemical Physics|April 27, 2023
Fast uncertainty estimates in deep learning interatomic potentialsAlbert Zhu, Simon Batzner, Albert Musaelian, et al.
Nature Communications|February 3, 2023
Learning local equivariant representations for large-scale atomistic dynamicsAlbert Musaelian, Simon Batzner, Anders Johansson, et al.
ACS Omega|March 11, 2024
Accurate Surface and Finite-Temperature Bulk Properties of Lithium Metal at Large Scales Using Machine Learning Interaction PotentialsMgcini Keith Phuthi, Archie Mingze Yao, Simon Batzner, et al.
Nature Communications|April 29, 2025
Unified differentiable learning of electric responseStefano Falletta, Andrea Cepellotti, Anders Johansson, et al.
Nature Communications|May 4, 2022
E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentialsSimon Batzner, Albert Musaelian, Lixin Sun, et al.
Nature Machine Intelligence|January 29, 2025
The design space of E(3)-equivariant atom-centred interatomic potentialsIlyes Batatia, Simon Batzner, Dávid Péter Kovács, et al.
The Journal of Physical Chemistry Letters|July 18, 2024
Transferability and Accuracy of Ionic Liquid Simulations with Equivariant Machine Learning Interatomic PotentialsZachary A H Goodwin, Malia B Wenny, Julia H Yang, et al.
Journal of the American Chemical Society|August 15, 2020
Evolution of Metastable Structures at Bimetallic Surfaces from Microscopy and Machine-Learning Molecular DynamicsJin Soo Lim, Jonathan Vandermause, Matthijs A van Spronsen, et al.
Pageof 1