Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Simon Batzner

Showing results (1-10 of 11) with videos related to

Pageof 2
Sort By:
Nature Computational Science|January 4, 2024
Biasing energy surfaces towards the unknownSimon Batzner
The Journal of Chemical Physics|April 27, 2023
Fast uncertainty estimates in deep learning interatomic potentialsAlbert Zhu, Simon Batzner, Albert Musaelian, et al.
Nature Computational Science|December 18, 2024
Predicting emergence of crystals from amorphous precursors with deep learning potentialsMuratahan Aykol, Amil Merchant, Simon Batzner, et al.
Nature|November 29, 2023
Scaling deep learning for materials discoveryAmil Merchant, Simon Batzner, Samuel S Schoenholz, et al.
Journal of Chemical Theory and Computation|March 11, 2022
Multitask Machine Learning of Collective Variables for Enhanced Sampling of Rare EventsLixin Sun, Jonathan Vandermause, Simon Batzner, 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|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.
Journal of the American Chemical Society|October 16, 2024
Efficient Exploratory Synthesis of Quaternary Cesium Chlorides Guided by In Silico PredictionsAkira Miura, Muratahan Aykol, Shumma Kozaki, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Nature Computational Science|January 4, 2024
Biasing energy surfaces towards the unknownSimon Batzner
The Journal of Chemical Physics|April 27, 2023
Fast uncertainty estimates in deep learning interatomic potentialsAlbert Zhu, Simon Batzner, Albert Musaelian, et al.
Nature Computational Science|December 18, 2024
Predicting emergence of crystals from amorphous precursors with deep learning potentialsMuratahan Aykol, Amil Merchant, Simon Batzner, et al.
Nature|November 29, 2023
Scaling deep learning for materials discoveryAmil Merchant, Simon Batzner, Samuel S Schoenholz, et al.
Journal of Chemical Theory and Computation|March 11, 2022
Multitask Machine Learning of Collective Variables for Enhanced Sampling of Rare EventsLixin Sun, Jonathan Vandermause, Simon Batzner, 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|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.
Journal of the American Chemical Society|October 16, 2024
Efficient Exploratory Synthesis of Quaternary Cesium Chlorides Guided by In Silico PredictionsAkira Miura, Muratahan Aykol, Shumma Kozaki, et al.
Pageof 2