35 citations · 74 across the 8 of their papers we have counts for
3 papers · 1 filter
Cluster expansion constructed over Jacobi-Legendre polynomials for accurate force fields
Michelangelo Domina, Urvesh Patil, Matteo Cobelli +1
We introduce a compact cluster expansion method, constructed over Jacobi and Legendre polynomials, to generate highly accurate and flexible machine-learning force fields. The const…
A spectral-neighbour representation for vector fields: machine-learning potentials including spin
Michelangelo Domina, Matteo Cobelli, Stefano Sanvito
We introduce a translational and rotational invariant local representation for vector fields, which can be employed in the construction of machine-learning energy models of solids…
Inversion of the chemical environment representations
Matteo Cobelli, Paddy Cahalane, Stefano Sanvito
Machine-learning generative methods for material design are constructed by representing a given chemical structure, either a solid or a molecule, over appropriate atomic features,…