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The Journal of Chemical Physics
|
April 15, 2023
SchNetPack 2.0: A neural network toolbox for atomistic machine learning
Kristof T Schütt, Stefaan S P Hessmann, Niklas W A Gebauer, et al.
Physical Chemistry Chemical Physics : PCCP
|
September 26, 2023
Automatic identification of chemical moieties
Jonas Lederer, Michael Gastegger, Kristof T Schütt, et al.
Nature Communications
|
February 22, 2022
Inverse design of 3d molecular structures with conditional generative neural networks
Niklas W A Gebauer, Michael Gastegger, Stefaan S P Hessmann, et al.
Nature Communications
|
December 15, 2021
SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects
Oliver T Unke, Stefan Chmiela, Michael Gastegger, et al.
Phytochemistry
|
June 6, 2015
Loganin and secologanin derived tryptamine-iridoid alkaloids from Palicourea crocea and Palicourea padifolia (Rubiaceae)
Andreas Berger, Maria Katharina Kostyan, Simon Immo Klose, et al.
Chemical Reviews
|
July 7, 2021
Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems
John A Keith, Valentin Vassilev-Galindo, Bingqing Cheng, et al.
Chemical Reviews
|
March 11, 2021
Machine Learning Force Fields
Oliver T Unke, Stefan Chmiela, Huziel E Sauceda, et al.
Science Advances
|
April 5, 2024
Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments
Oliver T Unke, Martin Stöhr, Stefan Ganscha, et al.
Arxiv
|
January 23, 2024
Improved motif-scaffolding with SE(3) flow matching
Jason Yim, Andrew Campbell, Emile Mathieu, et al.
Science (New York, N.Y.)
|
July 10, 2025
Scalable emulation of protein equilibrium ensembles with generative deep learning
Sarah Lewis, Tim Hempel, José Jiménez-Luna, et al.
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of 2
Search research articles
Search
Showing results (11-20 of 20) with videos related to
Sort By:
Page
of 2
You have reached the last page of results.
This site can display upto 20 results.
The Journal of Chemical Physics
|
April 15, 2023
SchNetPack 2.0: A neural network toolbox for atomistic machine learning
Kristof T Schütt, Stefaan S P Hessmann, Niklas W A Gebauer, et al.
Physical Chemistry Chemical Physics : PCCP
|
September 26, 2023
Automatic identification of chemical moieties
Jonas Lederer, Michael Gastegger, Kristof T Schütt, et al.
Nature Communications
|
February 22, 2022
Inverse design of 3d molecular structures with conditional generative neural networks
Niklas W A Gebauer, Michael Gastegger, Stefaan S P Hessmann, et al.
Nature Communications
|
December 15, 2021
SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects
Oliver T Unke, Stefan Chmiela, Michael Gastegger, et al.
Phytochemistry
|
June 6, 2015
Loganin and secologanin derived tryptamine-iridoid alkaloids from Palicourea crocea and Palicourea padifolia (Rubiaceae)
Andreas Berger, Maria Katharina Kostyan, Simon Immo Klose, et al.
Chemical Reviews
|
July 7, 2021
Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems
John A Keith, Valentin Vassilev-Galindo, Bingqing Cheng, et al.
Chemical Reviews
|
March 11, 2021
Machine Learning Force Fields
Oliver T Unke, Stefan Chmiela, Huziel E Sauceda, et al.
Science Advances
|
April 5, 2024
Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments
Oliver T Unke, Martin Stöhr, Stefan Ganscha, et al.
Arxiv
|
January 23, 2024
Improved motif-scaffolding with SE(3) flow matching
Jason Yim, Andrew Campbell, Emile Mathieu, et al.
Science (New York, N.Y.)
|
July 10, 2025
Scalable emulation of protein equilibrium ensembles with generative deep learning
Sarah Lewis, Tim Hempel, José Jiménez-Luna, et al.
Page
of 2