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Detecting unusual input to neural networks

Detecting unusual input to neural networks

Jörg Martin
Clemens Elster
    AAML
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Papers citing "Detecting unusual input to neural networks"

4 / 4 papers shown
Title
Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements
Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements
L. Hoffmann
I. Fortmeier
Clemens Elster
UQCV
17
28
0
01 Mar 2021
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
251
3,683
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
276
5,660
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
285
9,136
0
06 Jun 2015