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Rapid detection and recognition of whole brain activity in a freely behaving Caenorhabditis elegans


Sep 23, 2021
Yuxiang Wu, Shang Wu, Xin Wang, Chengtian Lang, Quanshi Zhang, Quan Wen, Tianqi Xu


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Interpreting Attributions and Interactions of Adversarial Attacks


Aug 16, 2021
Xin Wang, Shuyun Lin, Hao Zhang, Yufei Zhu, Quanshi Zhang


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A Hypothesis for the Aesthetic Appreciation in Neural Networks


Jul 31, 2021
Xu Cheng, Xin Wang, Haotian Xue, Zhengyang Liang, Quanshi Zhang


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Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI


Jul 26, 2021
Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang


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Interpretable Compositional Convolutional Neural Networks


Jul 09, 2021
Wen Shen, Zhihua Wei, Shikun Huang, Binbin Zhang, Jiaqi Fan, Ping Zhao, Quanshi Zhang

* IJCAI2021 

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A Game-Theoretic Taxonomy of Visual Concepts in DNNs


Jun 21, 2021
Xu Cheng, Chuntung Chu, Yi Zheng, Jie Ren, Quanshi Zhang

* 12 pages 

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Learning Baseline Values for Shapley Values


May 22, 2021
Jie Ren, Zhanpeng Zhou, Qirui Chen, Quanshi Zhang


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Game-theoretic Understanding of Adversarially Learned Features


Mar 12, 2021
Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Xu Cheng, Xin Wang, Yiting Chen, Jie Shi, Quanshi Zhang


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Game-Theoretic Interactions of Different Orders


Oct 28, 2020
Hao Zhang, Xu Cheng, Yiting Chen, Quanshi Zhang


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Interpreting Multivariate Interactions in DNNs


Oct 15, 2020
Hao Zhang, Yichen Xie, Longjie Zheng, Die Zhang, Quanshi Zhang


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Interpreting and Boosting Dropout from a Game-Theoretic View


Oct 10, 2020
Hao Zhang, Sen Li, Yinchao Ma, Mingjie Li, Yichen Xie, Quanshi Zhang


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A Unified Approach to Interpreting and Boosting Adversarial Transferability


Oct 08, 2020
Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang


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Achieving Adversarial Robustness via Sparsity


Sep 11, 2020
Shufan Wang, Ningyi Liao, Liyao Xiang, Nanyang Ye, Quanshi Zhang


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Interpreting Hierarchical Linguistic Interactions in DNNs


Jun 29, 2020
Die Zhang, Huilin Zhou, Xiaoyi Bao, Da Huo, Ruizhao Chen, Xu Cheng, Hao Zhang, Mengyue Wu, Quanshi Zhang


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Interpreting and Disentangling Feature Components of Various Complexity from DNNs


Jun 29, 2020
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang


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Rotation-Equivariant Neural Networks for Privacy Protection


Jun 21, 2020
Hao Zhang, Yiting Chen, Haotian Ma, Xu Cheng, Qihan Ren, Liyao Xiang, Jie Shi, Quanshi Zhang

* arXiv admin note: text overlap with arXiv:2003.08365 

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Deep Quaternion Features for Privacy Protection


Mar 18, 2020
Hao Zhang, Yiting Chen, Liyao Xiang, Haotian Ma, Jie Shi, Quanshi Zhang


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Explaining Knowledge Distillation by Quantifying the Knowledge


Mar 07, 2020
Xu Cheng, Zhefan Rao, Yilan Chen, Quanshi Zhang


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Preventing Information Leakage with Neural Architecture Search


Dec 18, 2019
Shuang Zhang, Liyao Xiang, Congcong Li, Yixuan Wang, Zeyu Liu, Quanshi Zhang, Bo Li

* 14 pages, 6 figures, submitted to Mobihoc 2020 and is under review 

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Utility Analysis of Network Architectures for 3D Point Cloud Processing


Nov 20, 2019
Shikun Huang, Binbin Zhang, Wen Shen, Zhihua Wei, Quanshi Zhang


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3D-Rotation-Equivariant Quaternion Neural Networks


Nov 20, 2019
Binbin Zhang, Wen Shen, Shikun Huang, Zhihua Wei, Quanshi Zhang


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Towards a Unified Evaluation of Explanation Methods without Ground Truth


Nov 20, 2019
Hao Zhang, Jiayi Chen, Haotian Xue, Quanshi Zhang


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Knowledge Isomorphism between Neural Networks


Aug 05, 2019
Ruofan Liang, Tianlin Li, Longfei Li, Quanshi Zhang


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Quantifying Layerwise Information Discarding of Neural Networks


Jun 10, 2019
Haotian Ma, Yinqing Zhang, Fan Zhou, Quanshi Zhang


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Complex-Valued Neural Networks for Privacy Protection


Jan 28, 2019
Liyao Xiang, Haotian Ma, Hao Zhang, Yifan Zhang, Quanshi Zhang


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Proceedings of AAAI 2019 Workshop on Network Interpretability for Deep Learning


Jan 25, 2019
Quanshi Zhang, Lixin Fan, Bolei Zhou


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Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract)


Jan 21, 2019
Quanshi Zhang, Yu Yang, Ying Nian Wu

* In AAAI-19 Workshop on Network Interpretability for Deep Learning. arXiv admin note: substantial text overlap with arXiv:1805.07468 

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