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Journal Article

Controlled exploration of chemical space by machine learning of coarse-grained representations

MPS-Authors

Hoffmann,  Christian
Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society;

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Menichetti,  Roberto
Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society;

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Kanekal,  Kiran
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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Citation

Hoffmann, C., Menichetti, R., Kanekal, K., & Bereau, T. (2019). Controlled exploration of chemical space by machine learning of coarse-grained representations. Physical Review E, 100(3): 033302. doi:10.1103/PhysRevE.100.033302.


Cite as: https://hdl.handle.net/21.11116/0000-0004-AF17-E
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