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Robustness of Bayesian Neural Networks to Gradient-Based Attacks

Robustness of Bayesian Neural Networks to Gradient-Based Attacks

11 February 2020
Ginevra Carbone
Matthew Wicker
Luca Laurenti
A. Patané
Luca Bortolussi
G. Sanguinetti
    AAML
ArXivPDFHTML

Papers citing "Robustness of Bayesian Neural Networks to Gradient-Based Attacks"

5 / 55 papers shown
Title
Evaluating Robustness of Predictive Uncertainty Estimation: Are
  Dirichlet-based Models Reliable?
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
Anna-Kathrin Kopetzki
Bertrand Charpentier
Daniel Zügner
Sandhya Giri
Stephan Günnemann
23
45
0
28 Oct 2020
Assessing Robustness of Text Classification through Maximal Safe Radius
  Computation
Assessing Robustness of Text Classification through Maximal Safe Radius Computation
Emanuele La Malfa
Min Wu
Luca Laurenti
Benjie Wang
Anthony Hartshorn
Marta Z. Kwiatkowska
AAML
12
18
0
01 Oct 2020
Probabilistic Safety for Bayesian Neural Networks
Probabilistic Safety for Bayesian Neural Networks
Matthew Wicker
Luca Laurenti
A. Patané
Marta Z. Kwiatkowska
AAML
6
52
0
21 Apr 2020
Adversarial Robustness Guarantees for Random Deep Neural Networks
Adversarial Robustness Guarantees for Random Deep Neural Networks
Giacomo De Palma
B. Kiani
S. Lloyd
AAML
OOD
6
8
0
13 Apr 2020
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
270
5,660
0
05 Dec 2016
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