One key advantage to Dedenser's cluster based downsampling over simply applying Poisson disk downsampling to the entire chemical point cloud is the potential to capture all chemical singletons rather than simply reducing them to blue noise. Additionally, dense clusters would be represented proportionally, by volume or density in chemical space, rather than also being reduced to blue noise relatively with the rest of the chemical point cloud. This may be critical when downsampling libraries, such as those generated in a targeted manner. Per example, if one were to generate an initial chemical library via a Bayesian sampling process , areas with higher likelihoods from the fitted prior distribution may be desired for retention at a higher proportionality, yet still downsampled. Alternatively, if desired, the epsilon parameter for cluster selection in HDBSCAN can be increased to treat all data as one cluster, effectively performing Poisson disk downsampling on the entire chemical point cloud.