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8 results in Keywords: Kernel ridge regression

Theoretical and Computational Chemistry

Working Paper

Size-Extensive Molecular Machine Learning with Global Descriptors

Hyunwook Jung, Sina Stocker, Christian Kunkel, Harald Oberhofer, Byungchan Han, Karsten Reuter, Johannes T. Margraf

Version 1 posted 22 October 2019

821

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Theoretical and Computational Chemistry

Working Paper

Explicit learning of derivatives with the KREG and pKREG models on the example of accurate representation of molecular potential energy surfaces

Yi-Fan Hou, Fuchun Ge, Pavlo O. Dral

Version 1 posted 20 October 2022

323

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Citations

Theoretical and Computational Chemistry

Working Paper

Machine Learning for Absorption Cross Sections

Bao-Xin Xue, Mario Barbatti, Pavlo O. Dral

Version 2 posted 22 July 2020

690

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Theoretical and Computational Chemistry

Working Paper

A comparative study of different machine learning methods for dissipative quantum dynamics

Luis E. Herrera Rodr ́ıguez, Arif Ullah, Kennet J. Rueda Espinosa, Pavlo O. Dral, Alexei A. Kananenka

Version 2 posted 13 September 2022

253

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Theoretical and Computational Chemistry

Working Paper

Speeding up quantum dissipative dynamics of open systems with kernel methods

Arif Ullah, Pavlo O. Dral

Version 2 posted 27 September 2021

421

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Theoretical and Computational Chemistry

Working Paper

MLQD: A package for machine learning-based quantum dissipative dynamics

Arif Ullah, Pavlo O. Dral

Version 3 posted 20 September 2023

261

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Theoretical and Computational Chemistry

Working Paper

Machine Learning of Quasiparticle Energies in Molecules and Clusters

Onur Çaylak, Björn Baumeier

Version 1 posted 24 May 2021

284

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Physical Chemistry

Working Paper

Fast and accurate excited states predictions: Machine learning and diabatization

Štěpán Sršeň, O. Anatole von Lilienfeld, Petr Slavicek

Version 1 posted 26 May 2023

419

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8 results in Kernel ridge regression in Keywords: Kernel ridge regression

Size-Extensive Molecular Machine Learning with Global Descriptors

Explicit learning of derivatives with the KREG and pKREG models on the example of accurate representation of molecular potential energy surfaces

Machine Learning for Absorption Cross Sections

A comparative study of different machine learning methods for dissipative quantum dynamics

Speeding up quantum dissipative dynamics of open systems with kernel methods

MLQD: A package for machine learning-based quantum dissipative dynamics

Machine Learning of Quasiparticle Energies in Molecules and Clusters

Fast and accurate excited states predictions: Machine learning and diabatization

8 results in Keywords: Kernel ridge regression