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Aaron G Garrison

Showing results (1-10 of 6) with videos related to

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Journal of Chemical Theory and Computation|February 17, 2026
System-Specific Reparameterization of Density Functionals with Machine Learning: Application to Spin-Splitting Energies of Transition Metal ComplexesAaron G Garrison, Heather J Kulik
Proceedings of the National Academy of Sciences of the United States of America|October 6, 2025
Graph neural networks for predicting metal-ligand coordination of transition metal complexesJacob W Toney, Roland G St Michel, Aaron G Garrison, et al.
Journal of the American Chemical Society|December 16, 2025
Identifying Dynamic Metal-Ligand Coordination Modes with Ensemble LearningJacob W Toney, Roland G St Michel, Aaron G Garrison, et al.
Journal of Chemical Information and Modeling|December 4, 2023
Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data SetAaron G Garrison, Javier Heras-Domingo, John R Kitchin, et al.
Faraday Discussions|September 20, 2024
Leveraging natural language processing to curate the tmCAT, tmPHOTO, tmBIO, and tmSCO datasets of functional transition metal complexesIlia Kevlishvili, Roland G St Michel, Aaron G Garrison, et al.
Journal of Chemical Information and Modeling|February 25, 2026
molSimplify 2.0: Improved Structure Generation for Automating Discovery in Inorganic Molecular and Reticular ChemistryGianmarco G Terrones, Roland G St Michel, Jacob W Toney, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
Journal of Chemical Theory and Computation|February 17, 2026
System-Specific Reparameterization of Density Functionals with Machine Learning: Application to Spin-Splitting Energies of Transition Metal ComplexesAaron G Garrison, Heather J Kulik
Proceedings of the National Academy of Sciences of the United States of America|October 6, 2025
Graph neural networks for predicting metal-ligand coordination of transition metal complexesJacob W Toney, Roland G St Michel, Aaron G Garrison, et al.
Journal of the American Chemical Society|December 16, 2025
Identifying Dynamic Metal-Ligand Coordination Modes with Ensemble LearningJacob W Toney, Roland G St Michel, Aaron G Garrison, et al.
Journal of Chemical Information and Modeling|December 4, 2023
Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data SetAaron G Garrison, Javier Heras-Domingo, John R Kitchin, et al.
Faraday Discussions|September 20, 2024
Leveraging natural language processing to curate the tmCAT, tmPHOTO, tmBIO, and tmSCO datasets of functional transition metal complexesIlia Kevlishvili, Roland G St Michel, Aaron G Garrison, et al.
Journal of Chemical Information and Modeling|February 25, 2026
molSimplify 2.0: Improved Structure Generation for Automating Discovery in Inorganic Molecular and Reticular ChemistryGianmarco G Terrones, Roland G St Michel, Jacob W Toney, et al.
Pageof 1