Fabio E. A. Albertani

most citedGlobal descriptors of a water molecule for machine learning of potential energy surfaces

3 citations · 6 across the 2 of their papers we have counts for

collaborators

2 papers

physics.chem-ph2024★ 3 cited

Translational eigenstates of He@C $_{60}$ from four-dimensional \textit{ab initio} Potential Energy Surfaces interpolated using Gaussian Process Regression

K. Panchagnula, D. Graf, F. E. A. Albertani +1

We investigate the endofullerene system $^{3}$ He@C $_{60}$ with a four-dimensional Potential Energy Surface (PES) to include the three He translational degrees of freedom and C $_{60}$ …

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…

Translational eigenstates of He@C60​ from four-dimensional \textit{ab initio} Potential Energy Surfaces interpolated using Gaussian Process Regression

Global descriptors of a water molecule for machine learning of potential energy surfaces

Translational eigenstates of He@C $_{60}$ from four-dimensional \textit{ab initio} Potential Energy Surfaces interpolated using Gaussian Process Regression