Deep interpretable ensembles

no code implementations • 25 May 2022 • Lucas Kook, Andrea Götschi, Philipp FM Baumann, Torsten Hothorn, Beate Sick

We propose a novel transformation ensemble which aggregates probabilistic predictions with the guarantee to preserve interpretability and yield uniformly better predictions than the ensemble members on average.

Uncertainty Quantification