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Alice E A Allen

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

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Science Advances|May 6, 2022
Machine learning of material properties: Predictive and interpretable multilinear modelsAlice E A Allen, Alexandre Tkatchenko
The Journal of Chemical Physics|March 25, 2024
Toward transferable empirical valence bonds: Making classical force fields reactiveAlice E A Allen, Gábor Csányi
Journal of Chemical Theory and Computation|November 22, 2017
Harmonic Force Constants for Molecular Mechanics Force Fields via Hessian Matrix ProjectionAlice E A Allen, Michael C Payne, Daniel J Cole
Chemical Communications (Cambridge, England)|December 19, 2019
Modelling flexible protein-ligand binding in p38α MAP kinase using the QUBE force fieldJoshua T Horton, Alice E A Allen, Daniel J Cole
Journal of Chemical Information and Modeling|February 12, 2019
QUBEKit: Automating the Derivation of Force Field Parameters from Quantum MechanicsJoshua T Horton, Alice E A Allen, Leela S Dodda, et al.
ACS Omega|September 19, 2019
Development and Validation of the Quantum Mechanical Bespoke Protein Force FieldAlice E A Allen, Michael J Robertson, Michael C Payne, et al.
Journal of Chemical Theory and Computation|November 4, 2021
Linear Atomic Cluster Expansion Force Fields for Organic Molecules: Beyond RMSEDávid Péter Kovács, Cas van der Oord, Jiri Kucera, et al.
Journal of Chemical Information and Modeling|January 28, 2025
Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data AugmentationLuan G F Dos Santos, Benjamin T Nebgen, Alice E A Allen, et al.
Journal of Chemical Theory and Computation|February 2, 2024
Machine Learning Potentials with the Iterative Boltzmann Inversion: Training to ExperimentSakib Matin, Alice E A Allen, Justin Smith, et al.
Chemical Reviews|November 21, 2024
Data Generation for Machine Learning Interatomic Potentials and BeyondMaksim Kulichenko, Benjamin Nebgen, Nicholas Lubbers, et al.
Pageof 2

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

Sort By:
Pageof 2
Science Advances|May 6, 2022
Machine learning of material properties: Predictive and interpretable multilinear modelsAlice E A Allen, Alexandre Tkatchenko
The Journal of Chemical Physics|March 25, 2024
Toward transferable empirical valence bonds: Making classical force fields reactiveAlice E A Allen, Gábor Csányi
Journal of Chemical Theory and Computation|November 22, 2017
Harmonic Force Constants for Molecular Mechanics Force Fields via Hessian Matrix ProjectionAlice E A Allen, Michael C Payne, Daniel J Cole
Chemical Communications (Cambridge, England)|December 19, 2019
Modelling flexible protein-ligand binding in p38α MAP kinase using the QUBE force fieldJoshua T Horton, Alice E A Allen, Daniel J Cole
Journal of Chemical Information and Modeling|February 12, 2019
QUBEKit: Automating the Derivation of Force Field Parameters from Quantum MechanicsJoshua T Horton, Alice E A Allen, Leela S Dodda, et al.
ACS Omega|September 19, 2019
Development and Validation of the Quantum Mechanical Bespoke Protein Force FieldAlice E A Allen, Michael J Robertson, Michael C Payne, et al.
Journal of Chemical Theory and Computation|November 4, 2021
Linear Atomic Cluster Expansion Force Fields for Organic Molecules: Beyond RMSEDávid Péter Kovács, Cas van der Oord, Jiri Kucera, et al.
Journal of Chemical Information and Modeling|January 28, 2025
Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data AugmentationLuan G F Dos Santos, Benjamin T Nebgen, Alice E A Allen, et al.
Journal of Chemical Theory and Computation|February 2, 2024
Machine Learning Potentials with the Iterative Boltzmann Inversion: Training to ExperimentSakib Matin, Alice E A Allen, Justin Smith, et al.
Chemical Reviews|November 21, 2024
Data Generation for Machine Learning Interatomic Potentials and BeyondMaksim Kulichenko, Benjamin Nebgen, Nicholas Lubbers, et al.
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