Quanshi Zhang - RankMe

164 papers A* 56A 1Journal 104Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Attribution Explanations for Deep Neural Networks: A Theoretical Perspective. CoRR Huiqi Deng, Hongbin Pei, Quanshi Zhang, Mengnan Du
2025	J	`jnl`	Counting Hallucinations in Diffusion Models. CoRR Shuai Fu, Jian Zhou, Qi Chen, Huang Jing, Huy Anh Nguyen, Xiaohan Liu, Zhixiong Zeng, Lin Ma, Quanshi Zhang, Qi Wu
2025	J	`jnl`	Interpretable Rotation-Equivariant Multiary-Valued Network for Attribute Obfuscation. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Hao Zhang, Yiting Chen, Qihan Ren, Jie Ren, Xu Cheng, Liyao Xiang
2025	A*	`conf`	Monitoring Primitive Interactions During the Training of DNNs. AAAI Jie Ren, Xinhao Zheng, Jiyu Liu, Andrew Lizarraga, Ying Nian Wu, Liang Lin, Quanshi Zhang
2025	J	`jnl`	Randomness of Low-Layer Parameters Determines Confusing Samples in Terms of Interaction Representations of a DNN. CoRR Junpeng Zhang, Lei Cheng, Qing Li, Liang Lin, Quanshi Zhang
2025	J	`jnl`	Revisiting Generalization Power of a DNN in Terms of Symbolic Interactions. CoRR Lei Cheng, Junpeng Zhang, Qihan Ren, Quanshi Zhang
2025	J	`jnl`	Technical Report: Quantifying and Analyzing the Generalization Power of a DNN. CoRR Yuxuan He, Junpeng Zhang, Lei Cheng, Hongyuan Zhang, Quanshi Zhang
2025	J	`jnl`	The Interaction Bottleneck of Deep Neural Networks: Discovery, Proof, and Modulation. CoRR Huiqi Deng, Qihan Ren, Zhuofan Chen, Zhenyuan Cui, Wen Shen, Peng Zhang, Hongbin Pei, Quanshi Zhang
2025	A*	`conf`	Towards Attributions of Input Variables in a Coalition. ICML Xinhao Zheng, Huiqi Deng, Quanshi Zhang
2025	J	`jnl`	Towards the Resistance of Neural Network Watermarking to Fine-tuning. CoRR Ling Tang, Yuefeng Chen, Hui Xue, Quanshi Zhang
2025	J	`jnl`	Towards the first principles of explaining DNNs: interactions explain the learning dynamics. Frontiers Inf. Technol. Electron. Eng. Huilin Zhou, Qihan Ren, Junpeng Zhang, Quanshi Zhang
2024	J	`jnl`	Alignment Between the Decision-Making Logic of LLMs and Human Cognition: A Case Study on Legal LLMs. CoRR Lu Chen, Yuxuan Huang, Yixing Li, Yaohui Jin, Shuai Zhao, Zilong Zheng, Quanshi Zhang
2024	J	`jnl`	An Introspective Data Augmentation Method for Training Math Word Problem Solvers. IEEE ACM Trans. Audio Speech Lang. Process. Jinghui Qin, Zhongzhan Huang, Ying Zeng, Quanshi Zhang, Liang Lin
2024	A*	`conf`	Batch Normalization Is Blind to the First and Second Derivatives of the Loss. AAAI Zhanpeng Zhou, Wen Shen, Huixin Chen, Ling Tang, Yuefeng Chen, Quanshi Zhang
2024	A*	`conf`	Clarifying the Behavior and the Difficulty of Adversarial Training. AAAI Xu Cheng, Hao Zhang, Yue Xin, Wen Shen, Quanshi Zhang
2024	J	`jnl`	Defining and Extracting generalizable interaction primitives from DNNs. CoRR Lu Chen, Siyu Lou, Benhao Huang, Quanshi Zhang
2024	A*	`conf`	Defining and extracting generalizable interaction primitives from DNNs. ICLR Lu Chen, Siyu Lou, Benhao Huang, Quanshi Zhang
2024	J	`jnl`	Disentangling Regional Primitives for Image Generation. CoRR Zhengting Chen, Lei Cheng, Lianghui Ding, Quanshi Zhang
2024	A*	`conf`	Explaining Generalization Power of a DNN Using Interactive Concepts. AAAI Huilin Zhou, Hao Zhang, Huiqi Deng, Dongrui Liu, Wen Shen, Shih-Han Chan, Quanshi Zhang
2024	—	`conf`	Identifying Semantic Induction Heads to Understand In-Context Learning. ACL (Findings) Jie Ren, Qipeng Guo, Hang Yan, Dongrui Liu, Quanshi Zhang, Xipeng Qiu, Dahua Lin
2024	J	`jnl`	Interpretability of Neural Networks Based on Game-theoretic Interactions. Mach. Intell. Res. Huilin Zhou, Jie Ren, Huiqi Deng, Xu Cheng, Jinpeng Zhang, Quanshi Zhang
2024	J	`jnl`	Interpretable Rotation-Equivariant Quaternion Neural Networks for 3D Point Cloud Processing. IEEE Trans. Pattern Anal. Mach. Intell. Wen Shen, Zhihua Wei, Qihan Ren, Binbin Zhang, Shikun Huang, Jiaqi Fan, Quanshi Zhang
2024	A*	`conf`	Layerwise Change of Knowledge in Neural Networks. ICML Xu Cheng, Lei Cheng, Zhaoran Peng, Yang Xu, Tian Han, Quanshi Zhang
2024	J	`jnl`	Layerwise Change of Knowledge in Neural Networks. CoRR Xu Cheng, Lei Cheng, Zhaoran Peng, Yang Xu, Tian Han, Quanshi Zhang
2024	J	`jnl`	Learning to Prevent Input Leakages in the Mobile Cloud Inference. IEEE Trans. Mob. Comput. Liyao Xiang, Shuang Zhang, Quanshi Zhang
2024	J	`jnl`	Quantifying In-Context Reasoning Effects and Memorization Effects in LLMs. CoRR Siyu Lou, Yuntian Chen, Xiaodan Liang, Liang Lin, Quanshi Zhang
2024	A*	`conf`	Towards the Dynamics of a DNN Learning Symbolic Interactions. NeurIPS Qihan Ren, Junpeng Zhang, Yang Xu, Yue Xin, Dongrui Liu, Quanshi Zhang
2024	J	`jnl`	Towards the Dynamics of a DNN Learning Symbolic Interactions. CoRR Qihan Ren, Yang Xu, Junpeng Zhang, Yue Xin, Dongrui Liu, Quanshi Zhang
2024	J	`jnl`	Two-Phase Dynamics of Interactions Explains the Starting Point of a DNN Learning Over-Fitted Features. CoRR Junpeng Zhang, Qing Li, Liang Lin, Quanshi Zhang
2024	J	`jnl`	Unifying Fourteen Post-Hoc Attribution Methods With Taylor Interactions. IEEE Trans. Pattern Anal. Mach. Intell. Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang
2024	A*	`conf`	Where We Have Arrived in Proving the Emergence of Sparse Interaction Primitives in DNNs. ICLR Qihan Ren, Jiayang Gao, Wen Shen, Quanshi Zhang
2023	A*	`conf`	Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts. ICML Qihan Ren, Huiqi Deng, Yunuo Chen, Siyu Lou, Quanshi Zhang
2023	J	`jnl`	Bayesian Neural Networks Tend to Ignore Complex and Sensitive Concepts. CoRR Qihan Ren, Huiqi Deng, Yunuo Chen, Siyu Lou, Quanshi Zhang
2023	A*	`conf`	Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN? ICLR Jie Ren, Zhanpeng Zhou, Qirui Chen, Quanshi Zhang
2023	J	`jnl`	Can the Inference Logic of Large Language Models be Disentangled into Symbolic Concepts? CoRR Wen Shen, Lei Cheng, Yuxiao Yang, Mingjie Li, Quanshi Zhang
2023	J	`jnl`	Concept-Level Explanation for the Generalization of a DNN. CoRR Huilin Zhou, Hao Zhang, Huiqi Deng, Dongrui Liu, Wen Shen, Shih-Han Chan, Quanshi Zhang
2023	A*	`conf`	Defects of Convolutional Decoder Networks in Frequency Representation. ICML Ling Tang, Wen Shen, Zhanpeng Zhou, Yuefeng Chen, Quanshi Zhang
2023	A*	`conf`	Defining and Quantifying the Emergence of Sparse Concepts in DNNs. CVPR Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang
2023	J	`jnl`	Does a Neural Network Really Encode Symbolic Concept? CoRR Mingjie Li, Quanshi Zhang
2023	A*	`conf`	Does a Neural Network Really Encode Symbolic Concepts? ICML Mingjie Li, Quanshi Zhang
2023	J	`jnl`	Explaining How a Neural Network Play the Go Game and Let People Learn. CoRR Huilin Zhou, Huijie Tang, Mingjie Li, Hao Zhang, Zhenyu Liu, Quanshi Zhang
2023	A*	`conf`	HarsanyiNet: Computing Accurate Shapley Values in a Single Forward Propagation. ICML Lu Chen, Siyu Lou, Keyan Zhang, Jin Huang, Quanshi Zhang
2023	J	`jnl`	HarsanyiNet: Computing Accurate Shapley Values in a Single Forward Propagation. CoRR Lu Chen, Siyu Lou, Keyan Zhang, Jin Huang, Quanshi Zhang
2023	—	`conf`	Network Transplanting for the Functionally Modular Architecture. PRCV (3) Quanshi Zhang, Xu Cheng, Xin Wang, Yu Yang, Yingnian Wu
2023	J	`jnl`	Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Xu Cheng, Yilan Chen, Zhefan Rao
2023	J	`jnl`	Technical Note: Defining and Quantifying AND-OR Interactions for Faithful and Concise Explanation of DNNs. CoRR Mingjie Li, Quanshi Zhang
2023	J	`jnl`	Towards Attributions of Input Variables in a Coalition. CoRR Xinhao Zheng, Huiqi Deng, Quanshi Zhang
2023	A*	`conf`	Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities. NeurIPS Dongrui Liu, Huiqi Deng, Xu Cheng, Qihan Ren, Kangrui Wang, Quanshi Zhang
2023	J	`jnl`	Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions. CoRR Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang
2023	J	`jnl`	Where We Have Arrived in Proving the Emergence of Sparse Symbolic Concepts in AI Models. CoRR Qihan Ren, Jiayang Gao, Wen Shen, Quanshi Zhang
2022	J	`jnl`	Batch Normalization Is Blind to the First and Second Derivatives of the Loss. CoRR Zhanpeng Zhou, Wen Shen, Huixin Chen, Ling Tang, Quanshi Zhang
2022	J	`jnl`	Defects of Convolutional Decoder Networks in Frequency Representation. CoRR Ling Tang, Wen Shen, Zhanpeng Zhou, Yuefeng Chen, Quanshi Zhang
2022	A*	`conf`	Discovering and Explaining the Representation Bottleneck of DNNS. ICLR Huiqi Deng, Qihan Ren, Hao Zhang, Quanshi Zhang
2022	A	`conf`	Exploring Image Regions Not Well Encoded by an INN. AISTATS Zenan Ling, Fan Zhou, Meng Wei, Quanshi Zhang
2022	A*	`conf`	Interpretable Generative Adversarial Networks. AAAI Chao Li, Kelu Yao, Jin Wang, Boyu Diao, Yongjun Xu, Quanshi Zhang
2022	J	`jnl`	Proving Common Mechanisms Shared by Twelve Methods of Boosting Adversarial Transferability. CoRR Quanshi Zhang, Xin Wang, Jie Ren, Xu Cheng, Shuyun Lin, Yisen Wang, Xiangming Zhu
2022	A*	`conf`	Quantification and Analysis of Layer-wise and Pixel-wise Information Discarding. ICML Haotian Ma, Hao Zhang, Fan Zhou, Yinqing Zhang, Quanshi Zhang
2022	J	`jnl`	Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification. CoRR Quanshi Zhang, Xu Cheng, Yilan Chen, Zhefan Rao
2022	A*	`conf`	RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL. EMNLP Jiexing Qi, Jingyao Tang, Ziwei He, Xiangpeng Wan, Yu Cheng, Chenghu Zhou, Xinbing Wang, Quanshi Zhang, Zhouhan Lin
2022	J	`jnl`	RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL. CoRR Jiexing Qi, Jingyao Tang, Ziwei He, Xiangpeng Wan, Chenghu Zhou, Xinbing Wang, Quanshi Zhang, Zhouhan Lin
2022	J	`jnl`	Rapid detection and recognition of whole brain activity in a freely behaving Caenorhabditis elegans. PLoS Comput. Biol. Yuxiang Wu, Shang Wu, Xin Wang, Chengtian Lang, Quanshi Zhang, Quan Wen, Tianqi Xu
2022	A*	`conf`	Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs. ICML Jie Ren, Mingjie Li, Meng Zhou, Shih-Han Chan, Quanshi Zhang
2022	J	`jnl`	Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs. CoRR Jie Ren, Mingjie Li, Meng Zhou, Shih-Han Chan, Quanshi Zhang
2022	J	`jnl`	Why Adversarial Training of ReLU Networks Is Difficult? CoRR Xu Cheng, Hao Zhang, Yue Xin, Wen Shen, Jie Ren, Quanshi Zhang
2021	J	`jnl`	A Game-Theoretic Taxonomy of Visual Concepts in DNNs. CoRR Xu Cheng, Chuntung Chu, Yi Zheng, Jie Ren, Quanshi Zhang
2021	J	`jnl`	A Hypothesis for the Aesthetic Appreciation in Neural Networks. CoRR Xu Cheng, Xin Wang, Haotian Xue, Zhengyang Liang, Quanshi Zhang
2021	A*	`conf`	A Unified Approach to Interpreting and Boosting Adversarial Transferability. ICLR Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
2021	A*	`conf`	Building Interpretable Interaction Trees for Deep NLP Models. AAAI Die Zhang, Hao Zhang, Huilin Zhou, Xiaoyi Bao, Da Huo, Ruizhao Chen, Xu Cheng, Mengyue Wu, Quanshi Zhang
2021	J	`jnl`	Discovering and Explaining the Representation Bottleneck of DNNs. CoRR Huiqi Deng, Qihan Ren, Xu Chen, Hao Zhang, Jie Ren, Quanshi Zhang
2021	J	`jnl`	Extraction of an Explanatory Graph to Interpret a CNN. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Xin Wang, Ruiming Cao, Ying Nian Wu, Feng Shi, Song-Chun Zhu
2021	J	`jnl`	Game-theoretic Understanding of Adversarially Learned Features. CoRR Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Xu Cheng, Xin Wang, Yiting Chen, Jie Shi, Quanshi Zhang
2021	J	`jnl`	Interpretable CNNs for Object Classification. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Xin Wang, Ying Nian Wu, Huilin Zhou, Song-Chun Zhu
2021	A*	`conf`	Interpretable Compositional Convolutional Neural Networks. IJCAI Wen Shen, Zhihua Wei, Shikun Huang, Binbin Zhang, Jiaqi Fan, Ping Zhao, Quanshi Zhang
2021	J	`jnl`	Interpretable Compositional Convolutional Neural Networks. CoRR Wen Shen, Zhihua Wei, Shikun Huang, Binbin Zhang, Jiaqi Fan, Ping Zhao, Quanshi Zhang
2021	A*	`conf`	Interpreting Attributions and Interactions of Adversarial Attacks. ICCV Xin Wang, Shuyun Lin, Hao Zhang, Yufei Zhu, Quanshi Zhang
2021	J	`jnl`	Interpreting Attributions and Interactions of Adversarial Attacks. CoRR Xin Wang, Shuyun Lin, Hao Zhang, Yufei Zhu, Quanshi Zhang
2021	A*	`conf`	Interpreting Multivariate Shapley Interactions in DNNs. AAAI Hao Zhang, Yichen Xie, Longjie Zheng, Die Zhang, Quanshi Zhang
2021	A*	`conf`	Interpreting Representation Quality of DNNs for 3D Point Cloud Processing. NeurIPS Wen Shen, Qihan Ren, Dongrui Liu, Quanshi Zhang
2021	J	`jnl`	Interpreting Representation Quality of DNNs for 3D Point Cloud Processing. CoRR Wen Shen, Qihan Ren, Dongrui Liu, Quanshi Zhang
2021	A*	`conf`	Interpreting and Boosting Dropout from a Game-Theoretic View. ICLR Hao Zhang, Sen Li, Yinchao Ma, Mingjie Li, Yichen Xie, Quanshi Zhang
2021	A*	`conf`	Interpreting and Disentangling Feature Components of Various Complexity from DNNs. ICML Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang
2021	J	`jnl`	Learning Baseline Values for Shapley Values. CoRR Jie Ren, Zhanpeng Zhou, Qirui Chen, Quanshi Zhang
2021	J	`jnl`	Mining Interpretable AOG Representations From Convolutional Networks via Active Question Answering. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Jie Ren, Ge Huang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2021	J	`jnl`	Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI. CoRR Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang
2021	J	`jnl`	Rapid detection and recognition of whole brain activity in a freely behaving Caenorhabditis elegans. CoRR Yuxiang Wu, Shang Wu, Xin Wang, Chengtian Lang, Quanshi Zhang, Quan Wen, Tianqi Xu
2021	J	`jnl`	Towards Axiomatic, Hierarchical, and Symbolic Explanation for Deep Models. CoRR Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang
2021	A*	`conf`	Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness. NeurIPS Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang
2021	J	`jnl`	Trap of Feature Diversity in the Learning of MLPs. CoRR Dongrui Liu, Shaobo Wang, Jie Ren, Kangrui Wang, Sheng Yin, Quanshi Zhang
2021	A*	`conf`	Verifiability and Predictability: Interpreting Utilities of Network Architectures for Point Cloud Processing. CVPR Wen Shen, Zhihua Wei, Shikun Huang, Binbin Zhang, Panyue Chen, Ping Zhao, Quanshi Zhang
2021	A*	`conf`	Visualizing the Emergence of Intermediate Visual Patterns in DNNs. NeurIPS Mingjie Li, Shaobo Wang, Quanshi Zhang
2021	J	`jnl`	Visualizing the Emergence of Intermediate Visual Patterns in DNNs. CoRR Mingjie Li, Shaobo Wang, Quanshi Zhang
2020	—	`conf`	3D-Rotation-Equivariant Quaternion Neural Networks. ECCV (20) Wen Shen, Binbin Zhang, Shikun Huang, Zhihua Wei, Quanshi Zhang
2020	J	`jnl`	A Unified Approach to Interpreting and Boosting Adversarial Transferability. CoRR Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
2020	J	`jnl`	Achieving Adversarial Robustness via Sparsity. CoRR Shufan Wang, Ningyi Liao, Liyao Xiang, Nanyang Ye, Quanshi Zhang
2020	J	`jnl`	Deep Quaternion Features for Privacy Protection. CoRR Hao Zhang, Yiting Chen, Liyao Xiang, Haotian Ma, Jie Shi, Quanshi Zhang
2020	A*	`conf`	Explaining Knowledge Distillation by Quantifying the Knowledge. CVPR Xu Cheng, Zhefan Rao, Yilan Chen, Quanshi Zhang
2020	J	`jnl`	Explaining Knowledge Distillation by Quantifying the Knowledge. CoRR Xu Cheng, Zhefan Rao, Yilan Chen, Quanshi Zhang
2020	J	`jnl`	Game-Theoretic Interactions of Different Orders. CoRR Hao Zhang, Xu Cheng, Yiting Chen, Quanshi Zhang
2020	A*	`conf`	Interpretable Complex-Valued Neural Networks for Privacy Protection. ICLR Liyao Xiang, Hao Zhang, Haotian Ma, Yifan Zhang, Jie Ren, Quanshi Zhang
2020	J	`jnl`	Interpreting Hierarchical Linguistic Interactions in DNNs. CoRR Die Zhang, Huilin Zhou, Xiaoyi Bao, Da Huo, Ruizhao Chen, Xu Cheng, Hao Zhang, Mengyue Wu, Quanshi Zhang
2020	J	`jnl`	Interpreting Multivariate Interactions in DNNs. CoRR Hao Zhang, Yichen Xie, Longjie Zheng, Die Zhang, Quanshi Zhang
2020	J	`jnl`	Interpreting and Boosting Dropout from a Game-Theoretic View. CoRR Hao Zhang, Sen Li, Yinchao Ma, Mingjie Li, Yichen Xie, Quanshi Zhang
2020	J	`jnl`	Interpreting and Disentangling Feature Components of Various Complexity from DNNs. CoRR Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang
2020	A*	`conf`	Knowledge Consistency between Neural Networks and Beyond. ICLR Ruofan Liang, Tianlin Li, Longfei Li, Jing Wang, Quanshi Zhang
2020	J	`jnl`	Rotation-Equivariant Neural Networks for Privacy Protection. CoRR Hao Zhang, Yiting Chen, Haotian Ma, Xu Cheng, Qihan Ren, Liyao Xiang, Jie Shi, Quanshi Zhang
2019	J	`jnl`	3D-Rotation-Equivariant Quaternion Neural Networks. CoRR Binbin Zhang, Wen Shen, Shikun Huang, Zhihua Wei, Quanshi Zhang
2019	J	`jnl`	Complex-Valued Neural Networks for Privacy Protection. CoRR Liyao Xiang, Haotian Ma, Hao Zhang, Yifan Zhang, Quanshi Zhang
2019	J	`jnl`	Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks. CoRR Zenan Ling, Haotian Ma, Yu Yang, Robert C. Qiu, Song-Chun Zhu, Quanshi Zhang
2019	A*	`conf`	Explaining Neural Networks Semantically and Quantitatively. ICCV Runjin Chen, Hao Chen, Ge Huang, Jie Ren, Quanshi Zhang
2019	J	`jnl`	Interpretable CNNs. CoRR Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2019	A*	`conf`	Interpreting CNNs via Decision Trees. CVPR Quanshi Zhang, Yu Yang, Haotian Ma, Ying Nian Wu
2019	J	`jnl`	Knowledge Isomorphism between Neural Networks. CoRR Ruofan Liang, Tianlin Li, Longfei Li, Quanshi Zhang
2019	J	`jnl`	Network Transplanting (extended abstract). CoRR Quanshi Zhang, Yu Yang, Qian Yu, Ying Nian Wu
2019	J	`jnl`	Preventing Information Leakage with Neural Architecture Search. CoRR Shuang Zhang, Liyao Xiang, Congcong Li, Yixuan Wang, Zeyu Liu, Quanshi Zhang, Bo Li
2019	J	`jnl`	Proceedings of AAAI 2019 Workshop on Network Interpretability for Deep Learning. CoRR Quanshi Zhang, Lixin Fan, Bolei Zhou
2019	J	`jnl`	Quantifying Layerwise Information Discarding of Neural Networks. CoRR Haotian Ma, Yinqing Zhang, Fan Zhou, Quanshi Zhang
2019	J	`jnl`	Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence. AI Mag. Guy Barash, Mauricio Castillo-Effen, Niyati Chhaya, Peter Clark, Huáscar Espinoza, Eitan Farchi, Christopher W. Geib, Odd Erik Gundersen, Seán Ó hÉigeartaigh, José Hernández-Orallo, Chiori Hori, Xiaowei Huang, Kokil Jaidka, Pavan Kapanipathi, Sarah Keren, Seokhwan Kim, Marc Lanctot, Danny Lange, Julian J. McAuley, David R. Martinez, Marwan Mattar, Mausam, Martin Michalowski, Reuth Mirsky, Roozbeh Mottaghi, Joseph C. Osborn, Julien Pérolat, Martin Schmid, Arash Shaban-Nejad, Onn Shehory, Biplav Srivastava, William W. Streilein, Kartik Talamadupula, Julian Togelius, Koichiro Yoshino, Quanshi Zhang, Imed Zitouni
2019	A*	`conf`	Towards a Deep and Unified Understanding of Deep Neural Models in NLP. ICML Chaoyu Guan, Xiting Wang, Quanshi Zhang, Runjin Chen, Di He, Xing Xie
2019	J	`jnl`	Towards a Unified Evaluation of Explanation Methods without Ground Truth. CoRR Hao Zhang, Jiayi Chen, Haotian Xue, Quanshi Zhang
2019	J	`jnl`	Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract). CoRR Quanshi Zhang, Yu Yang, Ying Nian Wu
2019	J	`jnl`	Utility Analysis of Network Architectures for 3D Point Cloud Processing. CoRR Shikun Huang, Binbin Zhang, Wen Shen, Zhihua Wei, Quanshi Zhang
2019	J	`jnl`	Visual graph mining for graph matching. Comput. Vis. Image Underst. Quanshi Zhang, Xuan Song, Yu Yang, Haotian Ma, Ryosuke Shibasaki
2018	A*	`conf`	Examining CNN Representations With Respect to Dataset Bias. AAAI Quanshi Zhang, Wenguan Wang, Song-Chun Zhu
2018	J	`jnl`	Explaining Neural Networks Semantically and Quantitatively. CoRR Runjin Chen, Hao Chen, Ge Huang, Jie Ren, Quanshi Zhang
2018	J	`jnl`	Explanatory Graphs for CNNs. CoRR Quanshi Zhang, Xin Wang, Ruiming Cao, Ying Nian Wu, Feng Shi, Song-Chun Zhu
2018	A*	`conf`	Interpretable Convolutional Neural Networks. CVPR Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2018	A*	`conf`	Interpreting CNN Knowledge via an Explanatory Graph. AAAI Quanshi Zhang, Ruiming Cao, Feng Shi, Ying Nian Wu, Song-Chun Zhu
2018	J	`jnl`	Interpreting CNNs via Decision Trees. CoRR Quanshi Zhang, Yu Yang, Ying Nian Wu, Song-Chun Zhu
2018	J	`jnl`	Mining Interpretable AOG Representations from Convolutional Networks via Active Question Answering. CoRR Quanshi Zhang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2018	J	`jnl`	Mining deep And-Or object structures via cost-sensitive question-answer-based active annotations. Comput. Vis. Image Underst. Quanshi Zhang, Ying Nian Wu, Hao Zhang, Song-Chun Zhu
2018	J	`jnl`	Network Transplanting. CoRR Quanshi Zhang, Yu Yang, Ying Nian Wu, Song-Chun Zhu
2018	J	`jnl`	Unsupervised Learning of Neural Networks to Explain Neural Networks. CoRR Quanshi Zhang, Yu Yang, Yuchen Liu, Ying Nian Wu, Song-Chun Zhu
2018	J	`jnl`	Visual Interpretability for Deep Learning: a Survey. CoRR Quanshi Zhang, Song-Chun Zhu
2018	J	`jnl`	Visual interpretability for deep learning: a survey. Frontiers Inf. Technol. Electron. Eng. Quanshi Zhang, Song-Chun Zhu
2017	J	`jnl`	A Cost-Sensitive Visual Question-Answer Framework for Mining a Deep And-OR Object Semantics from Web Images. CoRR Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Examining CNN representations with respect to Dataset Bias. CoRR Quanshi Zhang, Wenguan Wang, Song-Chun Zhu
2017	A*	`conf`	Growing Interpretable Part Graphs on ConvNets via Multi-Shot Learning. AAAI Quanshi Zhang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Interactively Transferring CNN Patterns for Part Localization. CoRR Quanshi Zhang, Ruiming Cao, Shengming Zhang, Mark Edmonds, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Interpretable Convolutional Neural Networks. CoRR Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Interpreting CNN knowledge via an Explanatory Graph. CoRR Quanshi Zhang, Ruiming Cao, Feng Shi, Ying Nian Wu, Song-Chun Zhu
2017	A*	`conf`	Mining Object Parts from CNNs via Active Question-Answering. CVPR Quanshi Zhang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Mining Object Parts from CNNs via Active Question-Answering. CoRR Quanshi Zhang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2017	J	`jnl`	Prediction and Simulation of Human Mobility Following Natural Disasters. ACM Trans. Intell. Syst. Technol. Xuan Song, Quanshi Zhang, Yoshihide Sekimoto, Ryosuke Shibasaki, Nicholas Jing Yuan, Xing Xie
2017	J	`jnl`	Visual Graph Mining. CoRR Quanshi Zhang, Xuan Song, Ryosuke Shibasaki
2016	J	`jnl`	Multi-Shot Mining Semantic Part Concepts in CNNs. CoRR Quanshi Zhang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
2016	J	`jnl`	Object Discovery: Soft Attributed Graph Mining. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Xuan Song, Xiaowei Shao, Huijing Zhao, Ryosuke Shibasaki
2015	A*	`conf`	A Simulator of Human Emergency Mobility Following Disasters: Knowledge Transfer from Big Disaster Data. AAAI Xuan Song, Quanshi Zhang, Yoshihide Sekimoto, Ryosuke Shibasaki, Nicholas Jing Yuan, Xing Xie
2015	J	`jnl`	From RGB-D Images to RGB Images: Single Labeling for Mining Visual Models. ACM Trans. Intell. Syst. Technol. Quanshi Zhang, Xuan Song, Xiaowei Shao, Huijing Zhao, Ryosuke Shibasaki
2015	A*	`conf`	Mining And-Or Graphs for Graph Matching and Object Discovery. ICCV Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2014	A*	`conf`	Attributed Graph Mining and Matching: An Attempt to Define and Extract Soft Attributed Patterns. CVPR Quanshi Zhang, Xuan Song, Xiaowei Shao, Huijing Zhao, Ryosuke Shibasaki
2014	A*	`conf`	Intelligent System for Urban Emergency Management during Large-Scale Disaster. AAAI Xuan Song, Quanshi Zhang, Yoshihide Sekimoto, Ryosuke Shibasaki
2014	A*	`conf`	Prediction of human emergency behavior and their mobility following large-scale disaster. KDD Xuan Song, Quanshi Zhang, Yoshihide Sekimoto, Ryosuke Shibasaki
2014	A*	`conf`	Start from minimum labeling: Learning of 3D object models and point labeling from a large and complex environment. ICRA Quanshi Zhang, Xuan Song, Xiaowei Shao, Huijing Zhao, Ryosuke Shibasaki
2014	A*	`conf`	When 3D Reconstruction Meets Ubiquitous RGB-D Images. CVPR Quanshi Zhang, Xuan Song, Xiaowei Shao, Huijing Zhao, Ryosuke Shibasaki
2013	J	`jnl`	A fully online and unsupervised system for large and high-density area surveillance: Tracking, semantic scene learning and abnormality detection. ACM Trans. Intell. Syst. Technol. Xuan Song, Xiaowei Shao, Quanshi Zhang, Ryosuke Shibasaki, Huijing Zhao, Jinshi Cui, Hongbin Zha
2013	J	`jnl`	A novel dynamic model for multiple pedestrians tracking in extremely crowded scenarios. Inf. Fusion Xuan Song, Xiaowei Shao, Quanshi Zhang, Ryosuke Shibasaki, Huijing Zhao, Hongbin Zha
2013	A*	`conf`	Category Modeling from Just a Single Labeling: Use Depth Information to Guide the Learning of 2D Models. CVPR Quanshi Zhang, Xuan Song, Xiaowei Shao, Ryosuke Shibasaki, Huijing Zhao
2013	J	`jnl`	Intelligent System for Human Behavior Analysis and Reasoning Following Large-Scale Disasters. IEEE Intell. Syst. Xuan Song, Quanshi Zhang, Yoshihide Sekimoto, Teerayut Horanont, Satoshi Ueyama, Ryosuke Shibasaki
2013	A*	`conf`	Learning Graph Matching: Oriented to Category Modeling from Cluttered Scenes. ICCV Quanshi Zhang, Xuan Song, Xiaowei Shao, Huijing Zhao, Ryosuke Shibasaki
2013	A*	`conf`	Modeling and probabilistic reasoning of population evacuation during large-scale disaster. KDD Xuan Song, Quanshi Zhang, Yoshihide Sekimoto, Teerayut Horanont, Satoshi Ueyama, Ryosuke Shibasaki
2013	A*	`conf`	Unsupervised 3D category discovery and point labeling from a large urban environment. ICRA Quanshi Zhang, Xuan Song, Xiaowei Shao, Huijing Zhao, Ryosuke Shibasaki
2013	J	`jnl`	Unsupervised skeleton extraction and motion capture from 3D deformable matching. Neurocomputing Quanshi Zhang, Xuan Song, Xiaowei Shao, Ryosuke Shibasaki, Huijing Zhao
2012	A*	`conf`	Laser-based intelligent surveillance and abnormality detection in extremely crowded scenarios. ICRA Xuan Song, Xiaowei Shao, Quanshi Zhang, Ryosuke Shibasaki, Huijing Zhao, Hongbin Zha
2009	A*	`conf`	Moving object classification using horizontal laser scan data. ICRA Huijing Zhao, Quanshi Zhang, Masaki Chiba, Ryosuke Shibasaki, Jinshi Cui, Hongbin Zha