Fig 3. Discovery of an optimally-separating latent feature space.

(Top Left) The high-dimensional and confounded raw inputs X makes class separation a challenging task.(Bottom Left) A case example including six microorganism species (A through F) which are entangled in the raw input space. (Top Right) A DL model which learns a latent space Z that optimally separates the classes. (Bottom Right) The disentanglement of the six species into distinct classes, which can be further aggregated into two major classes—Class 0 (A and B) and Class 1 (C through F).