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Pavlo O Dral

Showing results (21-30 of 82) with videos related to

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The Journal of Physical Chemistry. A|April 14, 2025
Accurate and Affordable Simulation of Molecular Infrared Spectra with AIQM ModelsYi-Fan Hou, Cheng Wang, Pavlo O Dral
Journal of Chemical Theory and Computation|July 7, 2015
Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical CalculationsPavlo O Dral, O Anatole von Lilienfeld, Walter Thiel
Scientific Data|February 15, 2023
WS22 database, Wigner Sampling and geometry interpolation for configurationally diverse molecular datasetsMax Pinheiro, Shuang Zhang, Pavlo O Dral, et al.
The Journal of Chemical Physics|June 4, 2020
Hierarchical machine learning of potential energy surfacesPavlo O Dral, Alec Owens, Alexey Dral, et al.
Chemical Science|February 2, 2026
Gradients not needed: ML-driven propagation of nonadiabatic molecular dynamics without reference gradientsMikołaj Martyka, Joanna Jankowska, Hans Lischka, et al.
Journal of Computational Chemistry|December 15, 2018
Big data analysis of ab Initio molecular integrals in the neglect of diatomic differential overlap approximationXin Wu, Pavlo O Dral, Axel Koslowski, et al.
Physical Chemistry Chemical Physics : PCCP|July 13, 2023
Themed collection on Insightful Machine Learning for Physical ChemistryAurora E Clark, Pavlo O Dral, Isaac Tamblyn, et al.
The Journal of Chemical Physics|July 3, 2017
Structure-based sampling and self-correcting machine learning for accurate calculations of potential energy surfaces and vibrational levelsPavlo O Dral, Alec Owens, Sergei N Yurchenko, et al.
Nature Communications|April 7, 2026
OMNI-P2x universal neural network potential for excited-state simulationsMikołaj Martyka, Xin-Yu Tong, Joanna Jankowska, et al.
Physical Chemistry Chemical Physics : PCCP|August 24, 2023
Energy-conserving molecular dynamics is not energy conservingLina Zhang, Yi-Fan Hou, Fuchun Ge, et al.
Pageof 9

Showing results (21-30 of 82) with videos related to

Sort By:
Pageof 9
The Journal of Physical Chemistry. A|April 14, 2025
Accurate and Affordable Simulation of Molecular Infrared Spectra with AIQM ModelsYi-Fan Hou, Cheng Wang, Pavlo O Dral
Journal of Chemical Theory and Computation|July 7, 2015
Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical CalculationsPavlo O Dral, O Anatole von Lilienfeld, Walter Thiel
Scientific Data|February 15, 2023
WS22 database, Wigner Sampling and geometry interpolation for configurationally diverse molecular datasetsMax Pinheiro, Shuang Zhang, Pavlo O Dral, et al.
The Journal of Chemical Physics|June 4, 2020
Hierarchical machine learning of potential energy surfacesPavlo O Dral, Alec Owens, Alexey Dral, et al.
Chemical Science|February 2, 2026
Gradients not needed: ML-driven propagation of nonadiabatic molecular dynamics without reference gradientsMikołaj Martyka, Joanna Jankowska, Hans Lischka, et al.
Journal of Computational Chemistry|December 15, 2018
Big data analysis of ab Initio molecular integrals in the neglect of diatomic differential overlap approximationXin Wu, Pavlo O Dral, Axel Koslowski, et al.
Physical Chemistry Chemical Physics : PCCP|July 13, 2023
Themed collection on Insightful Machine Learning for Physical ChemistryAurora E Clark, Pavlo O Dral, Isaac Tamblyn, et al.
The Journal of Chemical Physics|July 3, 2017
Structure-based sampling and self-correcting machine learning for accurate calculations of potential energy surfaces and vibrational levelsPavlo O Dral, Alec Owens, Sergei N Yurchenko, et al.
Nature Communications|April 7, 2026
OMNI-P2x universal neural network potential for excited-state simulationsMikołaj Martyka, Xin-Yu Tong, Joanna Jankowska, et al.
Physical Chemistry Chemical Physics : PCCP|August 24, 2023
Energy-conserving molecular dynamics is not energy conservingLina Zhang, Yi-Fan Hou, Fuchun Ge, et al.
Pageof 9