We used DeepChem 42 library to train the GCN models. Unlike other models, GCN uses its own featurization method instead of ECFC. We employed ConvMolFeaturizer class which implements Duvenaud graph convolutions to encode the molecules. We trained the GCN model with the default parameters except for adding a dropout of 0.25 and a batch size of 100. We trained the model for 100 epochs and the best epoch state is selected based on the performance over 20 percent of the reserved validation set from the training set.