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ORCIDTianxiang Zhao
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2020 – today
- 2025
[i22]Weijieying Ren, Tianxiang Zhao, Yuqing Huang, Vasant G. Honavar:
Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions. CoRR abs/2501.03540 (2025)- 2024
- [j7]Enyan Dai
, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang:
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. Mach. Intell. Res. 21(6): 1011-1061 (2024) - [j6]Dongsheng Luo, Tianxiang Zhao, Wei Cheng, Dongkuan Xu, Feng Han, Wenchao Yu, Xiao Liu, Haifeng Chen, Xiang Zhang:
Towards Inductive and Efficient Explanations for Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 46(8): 5245-5259 (2024) - [j5]Tianxiang Zhao, Haicheng Tu, Rui Jin, Yongxiang Xia, Fangfang Wang:
Improving resilience of cyber-physical power systems against cyber attacks through strategic energy storage deployment. Reliab. Eng. Syst. Saf. 252: 110438 (2024) - [j4]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Imbalanced Node Classification With Synthetic Over-Sampling. IEEE Trans. Knowl. Data Eng. 36(12): 8515-8528 (2024) - [c24]Huaisheng Zhu, Zongyu Wu, Tianxiang Zhao, Suhang Wang:
AmGNN: A Framework for Adaptive Processing of Inter-layer Information in Multi-layer Graph. ASONAM (1) 2024: 472-488 - [c23]Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang:
HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CIKM 2024: 2326-2335 - [c22]Jipeng Guo, Tengxiao Yin, Tianxiang Zhao, Jiayi Zhao, Yanfeng Sun, Junbin Gao, Youqing Wang:
Improved Attributed Graph Clustering with Representation and Structure Augmentation. IJCNN 2024: 1-8 - [c21]Tianxiang Zhao, Shoudong Shi, Kedi Qiu, Yongfang Ye, Ting Lan:
FSMANet: Flash Shuffle Mix Attention Network for Human Sitting Posture Recognition. IJCNN 2024: 1-8 - [c20]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. KDD 2024: 4479-4489 - [c19]Kedi Qiu, Shoudong Shi, Tianxiang Zhao, Yongfang Ye:
SCFormer: A Vision Transformer with Split Channel in Sitting Posture Recognition. MMM (1) 2024: 41-52 - [c18]Fali Wang, Tianxiang Zhao, Suhang Wang:
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. WSDM 2024: 712-720 - [c17]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Interpretable Imitation Learning with Dynamic Causal Relations. WSDM 2024: 967-975 - [c16]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Disambiguated Node Classification with Graph Neural Networks. WWW 2024: 914-923 - [i21]Fali Wang, Tianxiang Zhao, Suhang Wang:
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. CoRR abs/2401.10394 (2024) - [i20]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Disambiguated Node Classification with Graph Neural Networks. CoRR abs/2402.08824 (2024) - [i19]Weijieying Ren, Xinlong Li, Lei Wang, Tianxiang Zhao, Wei Qin:
Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning. CoRR abs/2402.18865 (2024) - [i18]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. CoRR abs/2406.10425 (2024) - [i17]Quan Li, Tianxiang Zhao, Lingwei Chen, Junjie Xu, Suhang Wang:
Enhancing Data-Limited Graph Neural Networks by Actively Distilling Knowledge from Large Language Models. CoRR abs/2407.13989 (2024) - [i16]Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang:
HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CoRR abs/2407.17787 (2024) - [i15]Haitong Luo, Xuying Meng, Suhang Wang, Tianxiang Zhao, Fali Wang, Hanyun Cao, Yujun Zhang:
Enhance Graph Alignment for Large Language Models. CoRR abs/2410.11370 (2024) - 2023
- [j3]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. ACM Trans. Intell. Syst. Technol. 14(5): 92:1-92:23 (2023) - [c15]Weijieying Ren, Tianxiang Zhao, Wei Qin, Kunpeng Liu:
T-SaS: Toward Shift-aware Dynamic Adaptation for Streaming Data. CIKM 2023: 4244-4248 - [c14]Yongfang Ye, Shoudong Shi, Tianxiang Zhao, Kedi Qiu, Ting Lan:
Patches Channel Attention for Human Sitting Posture Recognition. ICANN (10) 2023: 358-370 - [c13]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. KDD 2023: 3513-3524 - [c12]Huaisheng Zhu, Xianfeng Tang, Tianxiang Zhao, Suhang Wang:
You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural Network. PAKDD (2) 2023: 40-52 - [c11]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Towards Faithful and Consistent Explanations for Graph Neural Networks. WSDM 2023: 634-642 - [i14]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. CoRR abs/2301.02791 (2023) - [i13]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. CoRR abs/2306.07919 (2023) - [i12]Weijieying Ren, Tianxiang Zhao, Wei Qin, Kunpeng Liu:
T-SaS: Toward Shift-aware Dynamic Adaptation for Streaming Data. CoRR abs/2309.02610 (2023) - [i11]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Dynamic DAG Discovery for Interpretable Imitation Learning. CoRR abs/2310.00489 (2023) - 2022
- [j2]Yuhe Zhao, Minyu Wang, Tianxiang Zhao, Yi Luo, Yuhan Li, Kai Yan, Lei Lu, Ngoc Nguyen Tran, Xiaodan Wu, Xuanlong Ma:
Evaluating the potential of H8/AHI geostationary observations for monitoring vegetation phenology over different ecosystem types in northern China. Int. J. Appl. Earth Obs. Geoinformation 112: 102933 (2022) - [c10]Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao:
Explanation Guided Contrastive Learning for Sequential Recommendation. CIKM 2022: 2017-2027 - [c9]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
TopoImb: Toward Topology-Level Imbalance in Learning From Graphs. LoG 2022: 37 - [c8]Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang:
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features. WSDM 2022: 1433-1442 - [c7]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Exploring Edge Disentanglement for Node Classification. WWW 2022: 1028-1036 - [i10]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Exploring Edge Disentanglement for Node Classification. CoRR abs/2202.11245 (2022) - [i9]Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang:
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. CoRR abs/2204.08570 (2022) - [i8]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
On Consistency in Graph Neural Network Interpretation. CoRR abs/2205.13733 (2022) - [i7]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks. CoRR abs/2206.05335 (2022) - [i6]Lei Wang, Ee-Peng Lim, Zhiwei Liu, Tianxiang Zhao:
Explanation Guided Contrastive Learning for Sequential Recommendation. CoRR abs/2209.01347 (2022) - [i5]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
TopoImb: Toward Topology-level Imbalance in Learning from Graphs. CoRR abs/2212.08689 (2022) - 2021
- [j1]Weijieying Ren, Kunpeng Liu, Tianxiang Zhao, Yanjie Fu:
Fair and Effective Policing for Neighborhood Safety: Understanding and Overcoming Selection Biases. Frontiers Big Data 4: 787459 (2021) - [c6]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks. WSDM 2021: 833-841 - [i4]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks. CoRR abs/2103.08826 (2021) - [i3]Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang:
Semi-Supervised Graph-to-Graph Translation. CoRR abs/2103.08827 (2021) - [i2]Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang:
You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features. CoRR abs/2104.14537 (2021) - [i1]Yuqing Hu, Xiaoyuan Cheng, Suhang Wang, Jianli Chen, Tianxiang Zhao, Enyan Dai:
Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network. CoRR abs/2105.13399 (2021) - 2020
- [c5]Tianxiang Zhao, Lemao Liu, Guoping Huang, Huayang Li, Yingling Liu, Guiquan Liu, Shuming Shi:
Balancing Quality and Human Involvement: An Effective Approach to Interactive Neural Machine Translation. AAAI 2020: 9660-9667 - [c4]Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang:
Semi-Supervised Graph-to-Graph Translation. CIKM 2020: 1863-1872 - [c3]Amogh Subbakrishna Adishesha, Tianxiang Zhao:
Emotion Embedded Pose Generation. ECCV Workshops (1) 2020: 774-787
2010 – 2019
- 2018
- [c2]Tianxiang Zhao, Guiquan Liu, Le Wu, Chao Ma, Enhong Chen:
Zero-Shot Learning: An Energy Based Approach. ICDM 2018: 797-806 - [c1]Xiaoying Ren, Linli Xu, Tianxiang Zhao, Chen Zhu, Junliang Guo, Enhong Chen:
Tracking and Forecasting Dynamics in Crowdfunding: A Basis-Synthesis Approach. ICDM 2018: 1212-1217
Coauthor Index
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