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Jakob Gawlikowski

2 accepted papers

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…

2022

Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks

NeurIPS 2022accept

In image segmentation, the classic approach of learning a deterministic segmentation neither accounts for noise and ambiguity in the data nor for expert disagreements about the correct segmentation. This has been addressed by architectures that predict heteroscedastic (input-dependent) segmentation…

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