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

Félix Musil

Showing results (1-10 of 12) with videos related to

Pageof 2
Sort By:
Chimia|December 30, 2019
Machine Learning at the Atomic ScaleFélix Musil, Michele Ceriotti
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|April 22, 2019
Atom-density representations for machine learningMichael J Willatt, Félix Musil, Michele Ceriotti
The Journal of Chemical Physics|October 1, 2024
Accurate nuclear quantum statistics on machine-learned classical effective potentialsIryna Zaporozhets, Félix Musil, Venkat Kapil, et al.
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|September 16, 2021
Optimal radial basis for density-based atomic representationsAlexander Goscinski, Félix Musil, Sergey Pozdnyakov, et al.
The Journal of Chemical Physics|November 15, 2022
Quantum dynamics using path integral coarse-grainingFélix Musil, Iryna Zaporozhets, Frank Noé, et al.
Nature Communications|October 31, 2018
Chemical shifts in molecular solids by machine learningFederico M Paruzzo, Albert Hofstetter, Félix Musil, et al.
Chemical Science|April 21, 2018
Machine learning for the structure-energy-property landscapes of molecular crystalsFélix Musil, Sandip De, Jack Yang, et al.
The Journal of Chemical Physics|March 23, 2021
Efficient implementation of atom-density representationsFélix Musil, Max Veit, Alexander Goscinski, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Chimia|December 30, 2019
Machine Learning at the Atomic ScaleFélix Musil, Michele Ceriotti
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|April 22, 2019
Atom-density representations for machine learningMichael J Willatt, Félix Musil, Michele Ceriotti
The Journal of Chemical Physics|October 1, 2024
Accurate nuclear quantum statistics on machine-learned classical effective potentialsIryna Zaporozhets, Félix Musil, Venkat Kapil, et al.
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|September 16, 2021
Optimal radial basis for density-based atomic representationsAlexander Goscinski, Félix Musil, Sergey Pozdnyakov, et al.
The Journal of Chemical Physics|November 15, 2022
Quantum dynamics using path integral coarse-grainingFélix Musil, Iryna Zaporozhets, Frank Noé, et al.
Nature Communications|October 31, 2018
Chemical shifts in molecular solids by machine learningFederico M Paruzzo, Albert Hofstetter, Félix Musil, et al.
Chemical Science|April 21, 2018
Machine learning for the structure-energy-property landscapes of molecular crystalsFélix Musil, Sandip De, Jack Yang, et al.
The Journal of Chemical Physics|March 23, 2021
Efficient implementation of atom-density representationsFélix Musil, Max Veit, Alexander Goscinski, et al.
Pageof 2