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Statistical Guarantees for the Robustness of Bayesian Neural Networks

Statistical Guarantees for the Robustness of Bayesian Neural Networks

5 March 2019
L. Cardelli
M. Kwiatkowska
Luca Laurenti
Nicola Paoletti
A. Patané
Matthew Wicker
    AAML
ArXivPDFHTML

Papers citing "Statistical Guarantees for the Robustness of Bayesian Neural Networks"

12 / 12 papers shown
Title
Support is All You Need for Certified VAE Training
Support is All You Need for Certified VAE Training
Changming Xu
Debangshu Banerjee
Deepak Vasisht
Gagandeep Singh
AAML
39
0
0
16 Apr 2025
Probabilistic Verification of Neural Networks using Branch and Bound
Probabilistic Verification of Neural Networks using Branch and Bound
David Boetius
Stefan Leue
Tobias Sutter
42
0
0
27 May 2024
Distributionally Robust Statistical Verification with Imprecise Neural Networks
Distributionally Robust Statistical Verification with Imprecise Neural Networks
Souradeep Dutta
Michele Caprio
Vivian Lin
Matthew Cleaveland
Kuk Jin Jang
I. Ruchkin
O. Sokolsky
Insup Lee
OOD
AAML
49
7
0
28 Aug 2023
Making Substitute Models More Bayesian Can Enhance Transferability of
  Adversarial Examples
Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples
Qizhang Li
Yiwen Guo
W. Zuo
Hao Chen
AAML
27
35
0
10 Feb 2023
Make Sure You're Unsure: A Framework for Verifying Probabilistic
  Specifications
Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications
Leonard Berrada
Sumanth Dathathri
Krishnamurthy Dvijotham
Robert Stanforth
Rudy Bunel
J. Uesato
Sven Gowal
M. P. Kumar
AAML
OOD
30
17
0
18 Feb 2021
Probabilistic Guarantees for Safe Deep Reinforcement Learning
Probabilistic Guarantees for Safe Deep Reinforcement Learning
E. Bacci
David Parker
11
27
0
14 May 2020
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
29
77
0
11 Feb 2020
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
231
1,837
0
03 Feb 2017
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
M. Kwiatkowska
Sen Wang
Min Wu
AAML
180
932
0
21 Oct 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
9,138
0
06 Jun 2015
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,266
0
09 Jun 2012
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