We start by briefly introducing the most popular evaluation metrics, followed by a more in-depth discussion of each. The main assumption behind UQ is that the error (ε) of the ML prediction (y p ) is random and, therefore, follows a Gaussian distribution N with standard deviation σ. y py = ε ∼ N (0, σ 2 )