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Distilled probability regression model for heat reliability..:

, In: 12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE 2022),

Li, Q. ; Zheng, X. ; Zhou, W.... - p. None , 2022

Link: https://doi.org/10.1049/icp.2022.2886

RT 
T1 <cTitle>12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE 2022)</cTitle>: T1 <Title>Distilled probability regression model for heat reliability analysis</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10110566&Exemplar=1&LAN=DE
				
A1 Li, Q.
A1 Zheng, X.
A1 Zhou, W.
A1 Sun, J.
A1 Li, Y.
A1 Yao, W.
YR 2022
K1 aerospace computing
K1 artificial satellites
K1 avionics
K1 deep learning (artificial intelligence)
K1 heat
K1 image processing
K1 probability
K1 regression analysis
K1 reliability
K1 circuit board
K1 deep learning-based surrogate model
K1 distilled model
K1 distilled probability regression model
K1 ensemble
K1 heat layout
K1 heat reliability analysis
K1 image-to-image probabilistic regression task
K1 performance evaluation
K1 resource consumption
K1 satellite
K1 temperature field
K1 thermal environment
SP None
LK http://dx.doi.org/https://doi.org/10.1049/icp.2022.2886
DO https://doi.org/10.1049/icp.2022.2886
SF ELIB - SuUB Bremen

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