Information Divergence was originally developed as a method of comparing spectra to reference databases 70 and is adapted in Chemprop to be used as a loss function, considering the deviation of the spectrum as a whole rather than independently at each bin location. The treatment of spectra can handle targets with gaps or missing values within a dataset. With the expectation that spectra will often be collected in systems where a portion of the range will be obscured or invalid (e.g., from solvent absorbance), Chemprop can create exclusion regions in specified spectra where no predictions are provided and targets are ignored for training purposes.