Matthew Albert Chan

Estimating Epistemic and Aleatoric Uncertainty with a Single Model

Estimating and disentangling epistemic uncertainty, uncertainty that is reducible with more training data, and aleatoric uncertainty, uncertainty that is inherent to the task at hand, is critically important when applying machine learning to high-stakes applications such as medical imaging and weath…