One way to achieve this would be to work with full conformer ensembles rather than single conformers to construct the representations. It should also be noted that packing and contact effects occurring in molecular crystals or amorphous structures are known to influence the encountered solid-state conformation and flexibility for geometrical relaxation. Potentially, generative ML models trained on condensed phase data could therefore help producing more realistic conformer ensembles.