We start with the training using a set of hundreds of molecules randomly selected from the QMugs dataset (blue distribution in Figure ). These selected molecules will have band gap distribution similar to the QMugs dataset. We then query for HOMO-LUMO gaps, now around 1000 times requesting a molecule with a band gap taken from a normal distribution with shifted mean (mean 4 eV standard deviation 0.2 eV). We evaluated these new molecules (green curve in Figure ), which indeed shows a shift of the distribution to higher HOMO-LUMO gaps. In the next iteration, we retrain the model with the new data and query again higher HOMO-LUMO gaps. Figure shows that we have achieved our aim after four iterations.