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Provably Tightest Linear Approximation for Robustness Verification of
  Sigmoid-like Neural Networks

Provably Tightest Linear Approximation for Robustness Verification of Sigmoid-like Neural Networks

21 August 2022
Zhaodi Zhang
Yiting Wu
Siwen Liu
Jing Liu
Min Zhang
    AAML
ArXivPDFHTML

Papers citing "Provably Tightest Linear Approximation for Robustness Verification of Sigmoid-like Neural Networks"

4 / 4 papers shown
Title
Boosting Verified Training for Robust Image Classifications via
  Abstraction
Boosting Verified Training for Robust Image Classifications via Abstraction
Zhaodi Zhang
Zhiyi Xue
Yang Chen
Si Liu
Yueling Zhang
J. Liu
Min Zhang
26
4
0
21 Mar 2023
CNN-Cert: An Efficient Framework for Certifying Robustness of
  Convolutional Neural Networks
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
101
138
0
29 Nov 2018
Output Reachable Set Estimation and Verification for Multi-Layer Neural
  Networks
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks
Weiming Xiang
Hoang-Dung Tran
Taylor T. Johnson
72
292
0
09 Aug 2017
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
224
1,835
0
03 Feb 2017
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