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An Uncertainty-Informed Framework for Trustworthy Fault Diagnosis in Safety-Critical Applications

An Uncertainty-Informed Framework for Trustworthy Fault Diagnosis in Safety-Critical Applications

Taotao Zhou
E. Droguett
A. Mosleh
F. Chan
    EDL
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Papers citing "An Uncertainty-Informed Framework for Trustworthy Fault Diagnosis in Safety-Critical Applications"

4 / 4 papers shown
Title
Artificial intelligence approaches for materials-by-design of energetic materials: state-of-the-art, challenges, and future directions
Artificial intelligence approaches for materials-by-design of energetic materials: state-of-the-art, challenges, and future directions
Joseph B. Choi
Phong C. H. Nguyen
O. Sen
H. Udaykumar
Stephen Seung-Yeob Baek
PINN
AI4CE
29
11
0
15 Nov 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,683
0
05 Dec 2016
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Y. Gal
Zoubin Ghahramani
UQCV
BDL
207
745
0
06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
287
9,156
0
06 Jun 2015