On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks
Capturing aleatoric uncertainty is a critical part of many machine learning systems. In deep learning, a common approach to this end is to train a neural network to estimate the parameters of a hetero...
