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Adversarial Attacks Against Uncertainty Quantification

Adversarial Attacks Against Uncertainty Quantification

19 September 2023
Emanuele Ledda
Daniele Angioni
Giorgio Piras
Giorgio Fumera
Battista Biggio
Fabio Roli
    AAML
ArXivPDFHTML

Papers citing "Adversarial Attacks Against Uncertainty Quantification"

4 / 4 papers shown
Title
On the Robustness of Adversarial Training Against Uncertainty Attacks
On the Robustness of Adversarial Training Against Uncertainty Attacks
Emanuele Ledda
Giovanni Scodeller
Daniele Angioni
Giorgio Piras
Antonio Emanuele Cinà
Giorgio Fumera
Battista Biggio
Fabio Roli
AAML
28
1
0
29 Oct 2024
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors
Peter Lorenz
Mario Fernandez
Jens Müller
Ullrich Kothe
AAML
73
1
0
21 Jun 2024
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
5,652
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
247
9,109
0
06 Jun 2015
1