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Journal Article

Kernel-Based Machine Learning for Efficient Simulations of Molecular Liquids

MPS-Authors
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Scherer,  Christoph
Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society;

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Scheid,  René
Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society;

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Andrienko,  Denis
Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society;

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Bereau,  Tristan
Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society;
Emmy Noether Group Bereau: Biomolecular Simulations, MPI for Polymer Research, Max Planck Society;

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Fulltext (public)

acs.jctc.9b01256.pdf
(Publisher version), 2MB

Supplementary Material (public)
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Citation

Scherer, C., Scheid, R., Andrienko, D., & Bereau, T. (2020). Kernel-Based Machine Learning for Efficient Simulations of Molecular Liquids. Journal of Chemical Theory and Computation, 16(5), 3194-3204. doi:10.1021/acs.jctc.9b01256.


Cite as: http://hdl.handle.net/21.11116/0000-0006-6F12-A
Abstract
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