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Assessment of uncertainty quantification in universal differential equations. [PDF]

Philos Trans A Math Phys Eng Sci
Schmid N, Fernandes Del Pozo D, Waegeman W, Hasenauer J.   +3 more
europepmc   +1 more source

Uncertainty Quantification of Central Canal Stenosis Deep Learning Classifier from Lumbar Sagittal T2-Weighted MRI

Brenzikofer A, Monzon M, Galbusera F, Manjaly Z, Cina A, Jutzeler CR.   +5 more
europepmc   +1 more source

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Vehicle trajectory prediction considering aleatoric uncertainty

Knowledge-Based Systems, 2022
Hongyu Hu, Qi Wang, Laigang Du, Ziyang Lu, Zhenhai Gao   +4 more
openaire   +3 more sources

Distributional reinforcement learning with epistemic and aleatoric uncertainty estimation

Information Sciences, 2023
Qi Liu, Yanjie Li, Shiyu Chen, Ke Lin, Xiongtao Shi, Yunjiang Lou   +5 more
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Epistemic and Aleatoric Uncertainty in Modeling

Volume 8: 22nd Reliability, Stress Analysis, and Failure Prevention Conference; 25th Conference on Mechanical Vibration and Noise, 2013
One major difficulty that exists in reconciling model predictions of a system with experimental measurements is assessing and accounting for the uncertainties in the system. There are several enumerated sources of uncertainty in model prediction of physical phenomena, the primary ones being: 1) Model form error, 2) Aleatoric uncertainty of model ...
Daniel J. Segalman, Matthew R. Brake, Lawrence A. Bergman, Alexander F. Vakakis, Kai Willner   +4 more
openaire   +1 more source

Variational aleatoric uncertainty calibration in neural regression

2021
Des mesures de confiance calibrées et fiables sont un prérequis pour la plupart des systèmes de perception robotique car elles sont nécessaires aux modules de fusion de capteurs et de planification qui interviennent plus en aval. Cela est particulièrement vrai dans le cas d’applications où la sécurité est essentielle, comme les voitures à conduite ...
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Piecewise Linear Transformation – Propagating Aleatoric Uncertainty in Neural Networks

Proceedings of the AAAI Conference on Artificial Intelligence
Real-world data typically exhibit aleatoric uncertainty which has to be considered during data-driven decision-making to assess the confidence of the decision provided by machine learning models. To propagate aleatoric uncertainty represented by probability distributions (PDs) through neural networks (NNs), both sampling-based and function ...
Krapf, Thomas, Hagn, Michael, Miethaner, Paul, Schiller, Alexander, Luttner, Lucas, Heinrich, Bernd   +5 more
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Modeling Aleatoric Uncertainty for Camouflaged Object Detection

2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022
Jiawei Liu, Jing Zhang, Nick Barnes
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