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VeriX: Towards Verified Explainability of Deep Neural Networks.

, , и . CoRR, (2022)

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Jinglan Wu

Recovery of citric acid from fermentation broth using simulated moving bed technology: = Reinigung von Zitronensäure aus Fermentationslösung durch kontinuierliche Chromatographie. Uni Erlangen-Nürnberg, (2009)

Yinghua Wu

Jinjin Wu

Changzhu Wu

Haiyan Wu

 

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Global Optimization of Objective Functions Represented by ReLU Networks., , , , , , и . CoRR, (2020)Lemur: Integrating Large Language Models in Automated Program Verification., , и . CoRR, (2023)DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers., , , , , и . SAFECOMP, том 12852 из Lecture Notes in Computer Science, стр. 3-17. Springer, (2021)SAT Solving in the Serverless Cloud., , и . FMCAD, стр. 241-245. IEEE, (2021)Mutually Reinforced Spatio-Temporal Convolutional Tube for Human Action Recognition., , , , и . IJCAI, стр. 968-974. ijcai.org, (2019)Efficient Neural Network Analysis with Sum-of-Infeasibilities., , , и . TACAS (1), том 13243 из Lecture Notes in Computer Science, стр. 143-163. Springer, (2022)Cross-Fiber Spatial-Temporal Co-enhanced Networks for Video Action Recognition., , , , , и . ACM Multimedia, стр. 620-628. ACM, (2019)Convex Bounds on the Softmax Function with Applications to Robustness Verification., , , , , и . AISTATS, том 206 из Proceedings of Machine Learning Research, стр. 6853-6878. PMLR, (2023)An SMT-Based Approach for Verifying Binarized Neural Networks., , , и . TACAS (2), том 12652 из Lecture Notes in Computer Science, стр. 203-222. Springer, (2021)Proof-Stitch: Proof Combination for Divide-and-Conquer SAT Solvers., , , , и . FMCAD, стр. 84-88. IEEE, (2022)