Three machine learning architectures were employed within this study: i) directed message passing neural networks (d-MPNNs) as described by Yang et al. and implemented in the Chemprop software package 56 as a class of 2-dimensional graph-convolutional neural networks using learned representations, ii) feed-forward neural networks (FFNN) on molecular fingerprints, and iii) the 3dimensional convolutional neural network SchNet. Ensembles of five models were trained for each architecture and task if not specified otherwise.