Figure 6:

A schematic illustration of different uncertainty quantification methods. (A) Ensemble method by training k models with the same architectures but different weight initialization. (B) Monte Carlo dropout method by running the same model k times with probabilistic dropout for each run. (C) Evidential deep learning (EDL) method by training the model with EDL loss function.