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Jianlin Li
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Analyzing deep neural networks with symbolic propagation: Towards higher precision and faster verification
J Li, J Liu, P Yang, L Chen, X Huang, L Zhang
Static Analysis: 26th International Symposium, SAS 2019, Porto, Portugal …, 2019
902019
Improving neural network verification through spurious region guided refinement
P Yang, R Li, J Li, CC Huang, J Wang, J Sun, B Xue, L Zhang
International Conference on Tools and Algorithms for the Construction and …, 2021
422021
Prodeep: a platform for robustness verification of deep neural networks
R Li, J Li, CC Huang, P Yang, X Huang, L Zhang, B Xue, H Hermanns
Proceedings of the 28th ACM Joint Meeting on European Software Engineering …, 2020
252020
Enhancing robustness verification for deep neural networks via symbolic propagation
P Yang, J Li, J Liu, CC Huang, R Li, L Chen, X Huang, L Zhang
Formal Aspects of Computing 33 (3), 407-435, 2021
182021
Automated safety verification of programs invoking neural networks
M Christakis, HF Eniser, H Hermanns, J Hoffmann, Y Kothari, J Li, ...
Computer Aided Verification: 33rd International Conference, CAV 2021 …, 2021
102021
Type-preserving, dependence-aware guide generation for sound, effective amortized probabilistic inference
J Li, L Ven, P Shi, Y Zhang
Proceedings of the ACM on Programming Languages 7 (POPL), 1454-1482, 2023
22023
Verifying probabilistic timed automata against omega-regular dense-time properties
H Fu, Y Li, J Li
Quantitative Evaluation of Systems: 15th International Conference, QEST 2018 …, 2018
2018
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