A Appendix

A.1 Acetylacetone Dataset: Additional Experiments We ran additional experiments with the acetylacetone dataset introduced in [3] to further investigate the generalization capabilities of MACE [3]. Figure 4 shows the energy predictions of BOTNet [3], NequIP [5], MACE, and (linear) ACE [33] for two trajectories on the acetylacetone's potential energy surface (PES). The left panel shows the energy profile for a rotation around an O-C-C-C dihedral angle. Since the training set only contains dihedral angles below 30 (see lower panel), accurate predictions for angles up to 180 require significant extrapolation capabilities. Also the energy barrier of the rotation is with 1 eV well outside the energy range of the training set which is sampled at 300 K. It can be seen that all models solve this task surprisingly well.