522 citations · 1.7k across the 18 of their papers we have counts for
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Incorporating long-range physics in atomic-scale machine learning
Andrea Grisafi, Michele Ceriotti
The most successful and popular machine learning models of atomic-scale properties derive their transferability from a locality ansatz. The properties of a large molecule or a bulk…
Using Gaussian Process Regression to Simulate the Vibrational Raman Spectra of Molecular Crystals
Nathaniel Raimbault, Andrea Grisafi, Michele Ceriotti +1
Vibrational properties of molecular crystals are constantly used as structural fingerprints, in order to identify both the chemical nature and the structural arrangement of molecul…
Atomic-scale representation and statistical learning of tensorial properties
Andrea Grisafi, David M. Wilkins, Michael J. Willatt +1
This chapter discusses the importance of incorporating three-dimensional symmetries in the context of statistical learning models geared towards the interpolation of the tensorial…