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Electronic structure machine learning with SALTED
References
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    GitLab
    GitLab
    • Home
    • Installation
    • Theory
    • Workflow
    • Part 1 - Generate Training Data
    • Part 2 - Learn the Density
    • Part 3 - Predict Properties
    • Appendix
    • References

    References

    [1] A. M. Lewis, A. Grisafi, M. Ceriotti, and M. Rossi, Learning Electron Densities in the Condensed Phase, J. Chem. Theory Comput. 17, 7203 (2021).

    [2] A. Grisafi, A. M. Lewis, M. Rossi, and M. Ceriotti, Electronic-Structure Properties from Atom-Centered Predictions of the Electron Density, J. Chem. Theory Comput. acs.jctc.2c00850 (2023).

    [3] A. Grisafi, D. M. Wilkins, G. Csányi, and M. Ceriotti, Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems, Phys. Rev. Lett. 120, 036002 (2018).

    [4] M. J. Willatt, F. Musil, and M. Ceriotti, Atom-Density Representations for Machine Learning, J. Chem. Phys. 150, 154110 (2019)

    [5] A. M. Lewis, P. Lazzaroni, and M. Rossi, Predicting the Electronic Density Response of Condensed-Phase Systems to Electric Field Perturbations, The Journal of Chemical Physics 159, 014103 (2023).

    [6] A. P. Bartók, R. Kondor, and G. Csányi, On Representing Chemical Environments, Phys. Rev. B 87, 184115 (2013).

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