2019
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning
NeurIPS 2019poster
Ensemble learning is a standard approach to building machine learning systems that capture complex phenomena in real-world data. An important aspect of these systems is the complete and valid quantification of model uncertainty. We introduce a Bayesian nonparametric ensemble (BNE) approach that augm…