Search research articles
Contact Us
Filters
Showing results (1-10 of 10) with videos related to
Page
of 1
Sort By:
The Journal of Chemical Physics
|
August 8, 2023
Fast evaluation of spherical harmonics with sphericart
Filippo Bigi, Guillaume Fraux, Nicholas J Browning, et al.
The Journal of Chemical Physics
|
April 9, 2021
Machine learning of free energies in chemical compound space using ensemble representations: Reaching experimental uncertainty for solvation
Jan Weinreich, Nicholas J Browning, O Anatole von Lilienfeld
The Journal of Chemical Physics
|
December 13, 2022
GPU-accelerated approximate kernel method for quantum machine learning
Nicholas J Browning, Felix A Faber, O Anatole von Lilienfeld
The Journal of Physical Chemistry Letters
|
March 4, 2017
Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties
Nicholas J Browning, Raghunathan Ramakrishnan, O Anatole von Lilienfeld, et al.
The Journal of Chemical Physics
|
November 14, 2025
Machine learning-enhanced multiple time-step ab initio molecular dynamics
François Mouvet, Nicholas J Browning, Pablo Baudin, et al.
Journal of the American Chemical Society
|
January 17, 2018
Genetic Algorithm Based Design and Experimental Characterization of a Highly Thermostable Metalloprotein
Esra Bozkurt, Marta A S Perez, Ruud Hovius, et al.
Journal of the American Chemical Society
|
May 19, 2025
MACE-OFF: Short-Range Transferable Machine Learning Force Fields for Organic Molecules
Dávid Péter Kovács, J Harry Moore, Nicholas J Browning, et al.
Structural Dynamics (Melville, N.Y.)
|
January 30, 2018
Nonadiabatic effects in electronic and nuclear dynamics
Martin P Bircher, Elisa Liberatore, Nicholas J Browning, et al.
Chemical Science
|
February 12, 2025
Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023
Igor Poltavsky, Anton Charkin-Gorbulin, Mirela Puleva, et al.
Chemical Science
|
February 6, 2025
Crash testing machine learning force fields for molecules, materials, and interfaces: molecular dynamics in the TEA challenge 2023
Igor Poltavsky, Mirela Puleva, Anton Charkin-Gorbulin, et al.
Page
of 1
Search research articles
Search
Showing results (1-10 of 10) with videos related to
Sort By:
Page
of 1
The Journal of Chemical Physics
|
August 8, 2023
Fast evaluation of spherical harmonics with sphericart
Filippo Bigi, Guillaume Fraux, Nicholas J Browning, et al.
The Journal of Chemical Physics
|
April 9, 2021
Machine learning of free energies in chemical compound space using ensemble representations: Reaching experimental uncertainty for solvation
Jan Weinreich, Nicholas J Browning, O Anatole von Lilienfeld
The Journal of Chemical Physics
|
December 13, 2022
GPU-accelerated approximate kernel method for quantum machine learning
Nicholas J Browning, Felix A Faber, O Anatole von Lilienfeld
The Journal of Physical Chemistry Letters
|
March 4, 2017
Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties
Nicholas J Browning, Raghunathan Ramakrishnan, O Anatole von Lilienfeld, et al.
The Journal of Chemical Physics
|
November 14, 2025
Machine learning-enhanced multiple time-step ab initio molecular dynamics
François Mouvet, Nicholas J Browning, Pablo Baudin, et al.
Journal of the American Chemical Society
|
January 17, 2018
Genetic Algorithm Based Design and Experimental Characterization of a Highly Thermostable Metalloprotein
Esra Bozkurt, Marta A S Perez, Ruud Hovius, et al.
Journal of the American Chemical Society
|
May 19, 2025
MACE-OFF: Short-Range Transferable Machine Learning Force Fields for Organic Molecules
Dávid Péter Kovács, J Harry Moore, Nicholas J Browning, et al.
Structural Dynamics (Melville, N.Y.)
|
January 30, 2018
Nonadiabatic effects in electronic and nuclear dynamics
Martin P Bircher, Elisa Liberatore, Nicholas J Browning, et al.
Chemical Science
|
February 12, 2025
Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023
Igor Poltavsky, Anton Charkin-Gorbulin, Mirela Puleva, et al.
Chemical Science
|
February 6, 2025
Crash testing machine learning force fields for molecules, materials, and interfaces: molecular dynamics in the TEA challenge 2023
Igor Poltavsky, Mirela Puleva, Anton Charkin-Gorbulin, et al.
Page
of 1