2021
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
ICML 2021spotlight
Dirichlet-based uncertainty (DBU) models are a recent and promising class of uncertainty-aware models. DBU models predict the parameters of a Dirichlet distribution to provide fast, high-quality uncertainty estimates alongside with class predictions. In this work, we present the first large-scale, i…