and the number of hidden neurons (default 300) can be chosen by the user. The number of input neurons is set by the length of h m , and the number of output neurons by the number of targets. The activation function between linear layers is set to be the same as in the D-MPNN, and bias is turned on per default. For binary classification tasks, the final model output is passed through a sigmoid function to constrain values to the range (0,1). For multiclass classification, the final model output is transformed with a softmax function, such that the classification scores sum to 1 across classes.