Wenjie Ruan

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with Min Wu 0011

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Publications

2020
[j8]
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Xiaowei Huang, Daniel Kroening, Wenjie Ruan, James Sharp, Youcheng Sun, Emese Thamo, Min Wu, Xinping Yi:
A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability. Comput. Sci. Rev. 37: 100270 (2020)
[j7]
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  - journals/tcs/WuWRHK20
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Min Wu, Matthew Wicker, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska:
A game-based approximate verification of deep neural networks with provable guarantees. Theor. Comput. Sci. 807: 298-329 (2020)
2019
[c22]
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  - conf/ijcai/RuanWSHKK19
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Wenjie Ruan, Min Wu, Youcheng Sun, Xiaowei Huang, Daniel Kroening, Marta Kwiatkowska:
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Hamming Distance. IJCAI 2019: 5944-5952
[c21]
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  - conf/iros/WuLLRHMK19
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Min Wu, Tyron Louw, Morteza Lahijanian, Wenjie Ruan, Xiaowei Huang, Natasha Merat, Marta Kwiatkowska:
Gaze-based Intention Anticipation over Driving Manoeuvres in Semi-Autonomous Vehicles. IROS 2019: 6210-6216
2018
[c19]
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  - conf/kbse/SunWRHKK18
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Youcheng Sun, Min Wu, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska, Daniel Kroening:
Concolic testing for deep neural networks. ASE 2018: 109-119
[i4]
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  - journals/corr/abs-1804-05805
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Wenjie Ruan, Min Wu, Youcheng Sun, Xiaowei Huang, Daniel Kroening, Marta Kwiatkowska:
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for L0 Norm. CoRR abs/1804.05805 (2018)
[i3]
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  - journals/corr/abs-1805-00089
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Youcheng Sun, Min Wu, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska, Daniel Kroening:
Concolic Testing for Deep Neural Networks. CoRR abs/1805.00089 (2018)
[i1]
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  - journals/corr/abs-1807-03571
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Min Wu, Matthew Wicker, Wenjie Ruan, Xiaowei Huang, Marta Kwiatkowska:
A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees. CoRR abs/1807.03571 (2018)

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