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physics.chem-ph2023★ 3 cited
Global descriptors of a water molecule for machine learning of potential energy surfaces
Fabio E. A. Albertani, Alex J. W. Thom
Machine learning of multi-dimensional potential energy surfaces, from purely ab initio datasets, has seen substantial progress in the past years. Gaussian processes, a popular regr…
physics.chem-ph2023
Optimised Morse transform of a Gaussian process feature space
Fabio E. A. Albertani, Alex J. W. Thom
Morse projections are well-known in chemistry and allow one, within a Morse potential approximation, to redefine the potential in a simple quadratic form. The latter, being a non-l…
physics.chem-ph2022
Modified noise kernels in Gaussian process modelling of energy surfaces
Fabio E. A. Albertani, Alex J. W. Thom
We explore the use of non homogenous noise kernels in Gaussian process modelling to improve the potential energy curve models describing stochastic electronic structure data. We us…