The RBFE is dependent on the ordering of the ligands; if the ordering is swapped then the RBFE is multiplied by -1. Jiménez-Luna et al. claim that the latent space subtraction embeds this symmetry into the network architecture. We evaluate the utility of the latent space subtraction by concatenating rather than subtracting the latent spaces of the convolutional arms of the network. This requires that the fully connected layer of the network that predicts the RBFE doubles its input size. We further evaluate the importance of the Siamese network