781 citations · 836 across the 5 of their papers we have counts for
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Combining phonon accuracy with high transferability in Gaussian approximation potential models
Janine George, Geoffroy Hautier, Albert P. Bartók +2
Machine learning driven interatomic potentials, including Gaussian approximation potential (GAP) models, are emerging tools for atomistic simulations. Here, we address the methodol…
Efficient prediction of Nucleus Independent Chemical Shifts for polycyclic aromatic hydrocarbons
Dimitrios Kilymis, Albert P. Bartók, Chris J. Pickard +2
Nuclear Magnetic Resonance (NMR) is one of the most powerful experimental techniques to characterize the structure of molecules and confined liquids. Nevertheless, the complexity o…
On the Completeness of Atomic Structure Representations
Sergey N. Pozdnyakov, Michael J. Willatt, Albert P. Bartók +3
Many-body descriptors are widely used to represent atomic environments in the construction of machine learned interatomic potentials and more broadly for fitting, classification an…