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Michael J Willatt

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

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Physical Chemistry Chemical Physics : PCCP|November 23, 2018
Feature optimization for atomistic machine learning yields a data-driven construction of the periodic table of the elementsMichael J Willatt, Félix Musil, Michele Ceriotti
The Journal of Chemical Physics|January 9, 2022
Equivariant representations for molecular Hamiltonians and N-center atomic-scale propertiesJigyasa Nigam, Michael J Willatt, Michele Ceriotti
The Journal of Chemical Physics|April 22, 2019
Atom-density representations for machine learningMichael J Willatt, Félix Musil, Michele Ceriotti
The Journal of Chemical Physics|March 17, 2018
Approximating Matsubara dynamics using the planetary model: Tests on liquid water and iceMichael J Willatt, Michele Ceriotti, Stuart C Althorpe
Journal of Chemical Theory and Computation|January 4, 2019
Fast and Accurate Uncertainty Estimation in Chemical Machine LearningFélix Musil, Michael J Willatt, Mikhail A Langovoy, et al.
The Journal of Chemical Physics|April 10, 2015
Boltzmann-conserving classical dynamics in quantum time-correlation functions: "Matsubara dynamics"Timothy J H Hele, Michael J Willatt, Andrea Muolo, et al.
The Journal of Chemical Physics|May 24, 2015
Communication: Relation of centroid molecular dynamics and ring-polymer molecular dynamics to exact quantum dynamicsTimothy J H Hele, Michael J Willatt, Andrea Muolo, et al.
Physical Review Letters|October 30, 2020
Incompleteness of Atomic Structure RepresentationsSergey N Pozdnyakov, Michael J Willatt, Albert P Bartók, et al.
The Journal of Chemical Physics|November 8, 2022
Comment on "Manifolds of quasi-constant SOAP and ACSF fingerprints and the resulting failure to machine learn four-body interactions" [J. Chem. Phys. 156, 034302 (2022)]Sergey N Pozdnyakov, Michael J Willatt, Albert P Bartók, et al.
The Journal of Chemical Physics|March 23, 2021
Efficient implementation of atom-density representationsFélix Musil, Max Veit, Alexander Goscinski, et al.
Pageof 1

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

Sort By:
Pageof 1
Physical Chemistry Chemical Physics : PCCP|November 23, 2018
Feature optimization for atomistic machine learning yields a data-driven construction of the periodic table of the elementsMichael J Willatt, Félix Musil, Michele Ceriotti
The Journal of Chemical Physics|January 9, 2022
Equivariant representations for molecular Hamiltonians and N-center atomic-scale propertiesJigyasa Nigam, Michael J Willatt, Michele Ceriotti
The Journal of Chemical Physics|April 22, 2019
Atom-density representations for machine learningMichael J Willatt, Félix Musil, Michele Ceriotti
The Journal of Chemical Physics|March 17, 2018
Approximating Matsubara dynamics using the planetary model: Tests on liquid water and iceMichael J Willatt, Michele Ceriotti, Stuart C Althorpe
Journal of Chemical Theory and Computation|January 4, 2019
Fast and Accurate Uncertainty Estimation in Chemical Machine LearningFélix Musil, Michael J Willatt, Mikhail A Langovoy, et al.
The Journal of Chemical Physics|April 10, 2015
Boltzmann-conserving classical dynamics in quantum time-correlation functions: "Matsubara dynamics"Timothy J H Hele, Michael J Willatt, Andrea Muolo, et al.
The Journal of Chemical Physics|May 24, 2015
Communication: Relation of centroid molecular dynamics and ring-polymer molecular dynamics to exact quantum dynamicsTimothy J H Hele, Michael J Willatt, Andrea Muolo, et al.
Physical Review Letters|October 30, 2020
Incompleteness of Atomic Structure RepresentationsSergey N Pozdnyakov, Michael J Willatt, Albert P Bartók, et al.
The Journal of Chemical Physics|November 8, 2022
Comment on "Manifolds of quasi-constant SOAP and ACSF fingerprints and the resulting failure to machine learn four-body interactions" [J. Chem. Phys. 156, 034302 (2022)]Sergey N Pozdnyakov, Michael J Willatt, Albert P Bartók, et al.
The Journal of Chemical Physics|March 23, 2021
Efficient implementation of atom-density representationsFélix Musil, Max Veit, Alexander Goscinski, et al.
Pageof 1