We further compare the best performing D-MPNN model, multi-target learning, to other semi-empirical and data-driven models from the literature, as shown in Table . Specifically, we consider two GNN models that provide infinite dilution activity coefficient (AC) predictions, namely Gibbs-Duhem-informed (GDI)-GNNs trained on COSMO-RS activity coefficient data from our previous work and the Gibbs-Helmholtz (GH)-GNN trained on experimental infinite dilution activity coefficient (IDAC) data from the DECHEMA Chemistry Data Series . To predict the partition coefficients, we employ the already trained models from Ref. and Ref. , using Equation 3. We calculate the molar volumes with densities Tab. 3.