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1908.06353
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Verification of Neural Network Control Policy Under Persistent Adversarial Perturbation
18 August 2019
Yuh-Shyang Wang
Tsui-Wei Weng
Luca Daniel
AAML
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Papers citing
"Verification of Neural Network Control Policy Under Persistent Adversarial Perturbation"
9 / 9 papers shown
Title
A Survey of Neural Network Robustness Assessment in Image Recognition
Jie Wang
Jun Ai
Minyan Lu
Haoran Su
Dan Yu
Yutao Zhang
Junda Zhu
Jingyu Liu
AAML
30
3
0
12 Apr 2024
Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability
Mengdi Xu
Zuxin Liu
Peide Huang
Wenhao Ding
Zhepeng Cen
Bo-wen Li
Ding Zhao
74
45
0
16 Sep 2022
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review
Florian Tambon
Gabriel Laberge
Le An
Amin Nikanjam
Paulina Stevia Nouwou Mindom
Y. Pequignot
Foutse Khomh
G. Antoniol
E. Merlo
François Laviolette
30
66
0
26 Jul 2021
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS
Felix O. Olowononi
D. Rawat
Chunmei Liu
34
132
0
14 Feb 2021
SoK: Certified Robustness for Deep Neural Networks
Linyi Li
Tao Xie
Bo-wen Li
AAML
33
128
0
09 Sep 2020
Robust Deep Reinforcement Learning through Adversarial Loss
Tuomas P. Oikarinen
Wang Zhang
Alexandre Megretski
Luca Daniel
Tsui-Wei Weng
AAML
44
93
0
05 Aug 2020
Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning
Michael Everett
Bjorn Lutjens
Jonathan P. How
AAML
13
41
0
11 Apr 2020
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
Akhilan Boopathy
Tsui-Wei Weng
Pin-Yu Chen
Sijia Liu
Luca Daniel
AAML
108
138
0
29 Nov 2018
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
240
1,837
0
03 Feb 2017
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