Hierarchical Uncertainty Exploration via Feedforward Posterior Trees

In this work, we introduce a new approach for visualizing posteriors across multiple levels of granularity using tree -valued predictions. Our method predicts a tree-valued hierarchical summarization of the posterior distribution for any input measurement, in a single forward pass of a neural network.