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Nis Meinert

2 accepted papers

2024

Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?

ICML 2024poster

Trustworthy ML systems should not only return accurate predictions, but also a reliable representation of their uncertainty. Bayesian methods are commonly used to quantify both aleatoric and epistemic uncertainty, but alternative approaches, such as evidential deep learning methods, have become popu…

2023

The Unreasonable Effectiveness of Deep Evidential Regression

AAAI 2023technical

There is a significant need for principled uncertainty reasoning in machine learning systems as they are increasingly deployed in safety-critical domains. A new approach with uncertainty-aware regression-based neural networks (NNs), based on learning evidential distributions for aleatoric and episte…