Haoze Wu
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The marabou framework for verification and analysis of deep neural networks
G Katz, DA Huang, D Ibeling, K Julian, C Lazarus, R Lim, P Shah, ...
Computer Aided Verification: 31st International Conference, CAV 2019, New …, 2019
An SMT-Based Approach for Verifying Binarized Neural Networks
G Amir, H Wu, C Barrett, G Katz
Tools and Algorithms for the Construction and Analysis of Systems, 203-222, 2021
Parallelization techniques for verifying neural networks
H Wu, A Ozdemir, A Zeljić, K Julian, A Irfan, D Gopinath, S Fouladi, G Katz, ...
2020 Formal Methods in Computer Aided Design (FMCAD), 128-137, 2020
G2SAT: Learning to Generate SAT Formulas
J You, H Wu, C Barrett, R Ramanujan, J Leskovec
Advances in neural information processing systems, 10553-10564, 2019
Efficient neural network analysis with sum-of-infeasibilities
H Wu, A Zeljić, G Katz, C Barrett
International Conference on Tools and Algorithms for the Construction and …, 2022
Global optimization of objective functions represented by ReLU networks
CA Strong, H Wu, A Zeljić, KD Julian, G Katz, C Barrett, MJ Kochenderfer
Machine Learning, 2021
Toward certified robustness against real-world distribution shifts
H Wu, T Tagomori, A Robey, F Yang, N Matni, G Pappas, H Hassani, ...
2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 537-553, 2023
Deepcert: Verification of contextually relevant robustness for neural network image classifiers
C Paterson, H Wu, J Grese, R Calinescu, CS Păsăreanu, C Barrett
Computer Safety, Reliability, and Security: 40th International Conference …, 2021
Improving sat-solving with machine learning
H Wu
Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science …, 2017
Towards verification of neural networks for small unmanned aircraft collision avoidance
A Irfan, KD Julian, H Wu, C Barrett, MJ Kochenderfer, B Meng, J Lopez
2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC), 1-10, 2020
On reducing over-approximation errors for neural network verification
T Zelazny, H Wu, C Barrett, G Katz
Proc. 22nd Int. Conf. on Formal Methods in Computer-Aided Design (FMCAD), 17-26, 2022
Scalable verification of GNN-based job schedulers
H Wu, C Barrett, M Sharif, N Narodytska, G Singh
Proceedings of the ACM on Programming Languages 6 (OOPSLA2), 1036-1065, 2022
Verix: Towards verified explainability of deep neural networks
M Wu, H Wu, C Barrett
Advances in neural information processing systems 36, 2024
Learning to generate industrial sat instances
H Wu, R Ramanujan
Proceedings of the International Symposium on Combinatorial Search 10 (1 …, 2019
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks
H Wu, O Isac, A Zeljić, T Tagomori, M Daggitt, W Kokke, I Refaeli, G Amir, ...
arXiv preprint arXiv:2401.14461, 2024
Convex bounds on the softmax function with applications to robustness verification
D Wei, H Wu, M Wu, PY Chen, C Barrett, E Farchi
International Conference on Artificial Intelligence and Statistics, 6853-6878, 2023
Lemur: Integrating Large Language Models in Automated Program Verification
H Wu, C Barrett, N Narodytska
International Conference on Learning Representations, 2024
Towards Efficient Verification of Quantized Neural Networks
P Huang, H Wu, Y Yang, I Daukantas, M Wu, Y Zhang, C Barrett
Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 21152 …, 2024
Sat solving in the serverless cloud
A Ozdemir, H Wu, C Barrett
2021 Formal Methods in Computer Aided Design (FMCAD), 241-245, 2021
Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificates
U Mandal, G Amir, H Wu, I Daukantas, FL Newell, UJ Ravaioli, B Meng, ...
arXiv preprint arXiv:2405.14058, 2024
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