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Adversarial Phenomenon in the Eyes of Bayesian Deep Learning

Adversarial Phenomenon in the Eyes of Bayesian Deep Learning

22 November 2017
Ambrish Rawat
Martin Wistuba
Maria-Irina Nicolae
    BDL
    AAML
ArXivPDFHTML

Papers citing "Adversarial Phenomenon in the Eyes of Bayesian Deep Learning"

13 / 13 papers shown
Title
Logit Disagreement: OoD Detection with Bayesian Neural Networks
Logit Disagreement: OoD Detection with Bayesian Neural Networks
Kevin Raina
UQCV
BDL
UD
PER
66
0
0
24 Feb 2025
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural
  Networks
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks
Yunzhen Feng
Tim G. J. Rudner
Nikolaos Tsilivis
Julia Kempe
AAML
BDL
43
1
0
27 Apr 2024
LiBRe: A Practical Bayesian Approach to Adversarial Detection
LiBRe: A Practical Bayesian Approach to Adversarial Detection
Zhijie Deng
Xiao Yang
Shizhen Xu
Hang Su
Jun Zhu
BDL
AAML
25
61
0
27 Mar 2021
Probabilistic Safety for Bayesian Neural Networks
Probabilistic Safety for Bayesian Neural Networks
Matthew Wicker
Luca Laurenti
A. Patané
Marta Z. Kwiatkowska
AAML
14
52
0
21 Apr 2020
Robustness of Bayesian Neural Networks to Gradient-Based Attacks
Robustness of Bayesian Neural Networks to Gradient-Based Attacks
Ginevra Carbone
Matthew Wicker
Luca Laurenti
A. Patané
Luca Bortolussi
G. Sanguinetti
AAML
38
77
0
11 Feb 2020
Continual Learning Using Bayesian Neural Networks
Continual Learning Using Bayesian Neural Networks
Honglin Li
Payam Barnaghi
Shirin Enshaeifar
F. Ganz
BDL
19
38
0
09 Oct 2019
Statistical Guarantees for the Robustness of Bayesian Neural Networks
Statistical Guarantees for the Robustness of Bayesian Neural Networks
L. Cardelli
Marta Kwiatkowska
Luca Laurenti
Nicola Paoletti
A. Patané
Matthew Wicker
AAML
31
54
0
05 Mar 2019
Bayesian Adversarial Spheres: Bayesian Inference and Adversarial
  Examples in a Noiseless Setting
Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting
Artur Bekasov
Iain Murray
AAML
BDL
20
14
0
29 Nov 2018
Understanding Measures of Uncertainty for Adversarial Example Detection
Understanding Measures of Uncertainty for Adversarial Example Detection
Lewis Smith
Y. Gal
UQCV
57
358
0
22 Mar 2018
Explanation Methods in Deep Learning: Users, Values, Concerns and
  Challenges
Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges
Gabrielle Ras
Marcel van Gerven
W. Haselager
XAI
17
217
0
20 Mar 2018
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in
  Gaussian Process Hybrid Deep Networks
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks
John Bradshaw
A. G. Matthews
Zoubin Ghahramani
BDL
AAML
72
171
0
08 Jul 2017
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
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