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Explainability through uncertainty: Trustworthy decision-making with neural networks

Explainability through uncertainty: Trustworthy decision-making with neural networks

Arthur Thuy
Dries F. Benoit
ArXivPDFHTML

Papers citing "Explainability through uncertainty: Trustworthy decision-making with neural networks"

5 / 5 papers shown
Title
Generalizing Machine Learning Evaluation through the Integration of Shannon Entropy and Rough Set Theory
Generalizing Machine Learning Evaluation through the Integration of Shannon Entropy and Rough Set Theory
Olga Cherednichenko
Dmytro Chernyshov
Dmytro Sytnikov
Polina Sytnikova
31
0
0
18 Apr 2024
Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge
Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge
Xiaoge Zhang
Xiao-Lin Wang
Fenglei Fan
Yiu-ming Cheung
Indranil Bose
18
1
0
29 Nov 2023
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
219
3,658
0
28 Feb 2017
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
268
5,635
0
05 Dec 2016
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
245
9,042
0
06 Jun 2015