In this work, MLPs were trained using linear regression with the ACE descriptor and its variant MACE, in which ACE is combined with an equivariant message-passing neural network architecture. The ACE descriptor builds on a traditional many-body expansion, where the Potential Energy Surface (PES) of the system is expressed as a sum of different body-order interactions, including two-body, three-body, and higher-order interactions depending on the truncation.