Results 21 to 30 of about 7,687 (182)
Recalibration of Aleatoric and EpistemicRegression Uncertainty in Medical Imaging
Machine Learning for Biomedical Imaging, 2021 The consideration of predictive uncertainty in medical imaging with deep learning is of utmost importance. We apply estimation of both aleatoric and epistemic uncertainty by variational Bayesian inference with Monte Carlo dropout to regression tasks and show that predictive uncertainty is systematically underestimated.
Max-Heinrich Laves +4 more
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Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty
Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020 In image segmentation, there is often more than one plausible solution for a given input. In medical imaging, for example, experts will often disagree about the exact location of object boundaries. Estimating this inherent uncertainty and predicting multiple plausible hypotheses is of great interest in many applications, yet this ability is lacking in ...
Monteiro, M +7 more
openaire +3 more sources
Grounding Aleatoric Uncertainty for Unsupervised Environment Design
, 2022 NeurIPS ...
Jiang, Minqi +7 more
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Applied Sciences, 2021 Aleatoric and epistemic uncertainties can be represented probabilistically in mechanical systems. However, the distribution parameters of epistemic uncertainties are also uncertain due to sparsely available or inaccurate uncertainty information ...
Yufeng Lyu +4 more
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Cold Posteriors and Aleatoric Uncertainty
, 2020 5 pages, 3 ...
Adlam, Ben +2 more
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Towards Reliable Parameter Extraction in MEMS Final Module Testing Using Bayesian Inference
Sensors, 2022 In micro-electro-mechanical systems (MEMS) testing high overall precision and reliability are essential. Due to the additional requirement of runtime efficiency, machine learning methods have been investigated in recent years.
Monika E. Heringhaus +3 more
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A CLOSER LOOK AT SEGMENTATION UNCERTAINTY OF SCANNED HISTORICAL MAPS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Before modern earth observation techniques came into being, historical maps are almost the exclusive source to retrieve geo-spatial information on Earth.
S. Wu, M. Heitzler, L. Hurni
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Towards Reducing Aleatoric Uncertainty for Medical Imaging Tasks
2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 2022 Accepted in IEEE International Symposium on Biomedical Imaging (ISBI ...
Sambyal, Abhishek Singh +2 more
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Achieving robustness to aleatoric uncertainty with heteroscedastic Bayesian optimisation
Machine Learning: Science and Technology, 2021 Abstract Bayesian optimisation is a sample-efficient search methodology that holds great promise for accelerating drug and materials discovery programs. A frequently-overlooked modelling consideration in Bayesian optimisation strategies however, is the representation of heteroscedastic aleatoric uncertainty.
Griffiths, Ryan-Rhys +4 more
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Uncertainty Quantification for Full-Flight Data Based Engine Fault Detection with Neural Networks
Machines, 2022 Current state-of-the-art engine condition monitoring is based on a minimum of one steady-state data point per flight. Due to the scarcity of available data points, there are difficulties distinguishing between random scatter and an underlying fault ...
Matthias Weiss +4 more
doaj +1 more source