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Symbolic Execution for Deep Neural Networks

Symbolic Execution for Deep Neural Networks

27 July 2018
D. Gopinath
Kaiyuan Wang
Mengshi Zhang
C. Păsăreanu
S. Khurshid
    AAML
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Papers citing "Symbolic Execution for Deep Neural Networks"

14 / 14 papers shown
Title
A Survey of Safety and Trustworthiness of Large Language Models through
  the Lens of Verification and Validation
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation
Xiaowei Huang
Wenjie Ruan
Wei Huang
Gao Jin
Yizhen Dong
...
Sihao Wu
Peipei Xu
Dengyu Wu
André Freitas
Mustafa A. Mustafa
ALM
52
83
0
19 May 2023
Towards Rigorous Understanding of Neural Networks via
  Semantics-preserving Transformations
Towards Rigorous Understanding of Neural Networks via Semantics-preserving Transformations
Maximilian Schlüter
Gerrit Nolte
Alnis Murtovi
Bernhard Steffen
31
6
0
19 Jan 2023
Efficient Adversarial Input Generation via Neural Net Patching
Efficient Adversarial Input Generation via Neural Net Patching
Tooba Khan
Kumar Madhukar
Subodh Vishnu Sharma
AAML
24
0
0
30 Nov 2022
Safe Neurosymbolic Learning with Differentiable Symbolic Execution
Safe Neurosymbolic Learning with Differentiable Symbolic Execution
Chenxi Yang
Swarat Chaudhuri
29
9
0
15 Mar 2022
Importance-Driven Deep Learning System Testing
Importance-Driven Deep Learning System Testing
Simos Gerasimou
Hasan Ferit Eniser
A. Sen
Alper Çakan
AAML
VLM
32
98
0
09 Feb 2020
Metamorphic Testing for Object Detection Systems
Metamorphic Testing for Object Detection Systems
Shuai Wang
Z. Su
34
24
0
19 Dec 2019
DeepSmartFuzzer: Reward Guided Test Generation For Deep Learning
DeepSmartFuzzer: Reward Guided Test Generation For Deep Learning
Samet Demir
Hasan Ferit Eniser
A. Sen
AAML
11
28
0
24 Nov 2019
Coverage Guided Testing for Recurrent Neural Networks
Coverage Guided Testing for Recurrent Neural Networks
Wei Huang
Youcheng Sun
Xing-E. Zhao
James Sharp
Wenjie Ruan
Jie Meng
Xiaowei Huang
AAML
37
47
0
05 Nov 2019
Machine Learning Testing: Survey, Landscapes and Horizons
Machine Learning Testing: Survey, Landscapes and Horizons
Jie M. Zhang
Mark Harman
Lei Ma
Yang Liu
VLM
AILaw
39
741
0
19 Jun 2019
Automated Test Generation to Detect Individual Discrimination in AI
  Models
Automated Test Generation to Detect Individual Discrimination in AI Models
Aniya Aggarwal
P. Lohia
Seema Nagar
Kuntal Dey
Diptikalyan Saha
15
40
0
10 Sep 2018
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in
  Neural Networks
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks
D. Gopinath
Guy Katz
C. Păsăreanu
Clark W. Barrett
AAML
50
87
0
02 Oct 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
251
1,842
0
03 Feb 2017
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
309
3,115
0
04 Nov 2016
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
Marta Kwiatkowska
Sen Wang
Min Wu
AAML
183
933
0
21 Oct 2016
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