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Publication search results
found 55 matches
- 2024
- Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
Rethinking and Simplifying Bootstrapped Graph Latents. WSDM 2024: 665-673 - Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng:
The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. WSDM 2024: 1012-1021 - Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen:
Fair Graph Representation Learning via Sensitive Attribute Disentanglement. WWW 2024: 1182-1192 - Huizhe Zhang, Jintang Li, Liang Chen, Zibin Zheng:
SGHormer: An Energy-Saving Graph Transformer Driven by Spikes. CoRR abs/2403.17656 (2024) - 2023
- Xiangfei Feng, Wenjia Cai, Rongqin Zheng, Lina Tang, Jianhua Zhou, Hui Wang, Jintang Liao, Baoming Luo, Wen Cheng, An Wei, Weian Zhao, Xiang Jing, Ping Liang, Jie Yu, Qinghua Huang:
Diagnosis of hepatocellular carcinoma using deep network with multi-view enhanced patterns mined in contrast-enhanced ultrasound data. Eng. Appl. Artif. Intell. 118: 105635 (2023) - Yuncheng Wang, Jintang Xue, Chengwei Wei, C.-C. Jay Kuo:
An Overview on Generative AI at Scale With Edge-Cloud Computing. IEEE Open J. Commun. Soc. 4: 2952-2971 (2023) - Jintang Li, Jiaying Peng, Liang Chen, Zibin Zheng, Tingting Liang, Qing Ling:
Spectral Adversarial Training for Robust Graph Neural Network. IEEE Trans. Knowl. Data Eng. 35(9): 9240-9253 (2023) - Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng:
Adversarial Attack on Large Scale Graph. IEEE Trans. Knowl. Data Eng. 35(1): 82-95 (2023) - Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng:
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. AAAI 2023: 8588-8596 - Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Zibin Zheng, Jiawang Dan, Changhua Meng, Weiqiang Wang:
GUARD: Graph Universal Adversarial Defense. CIKM 2023: 1198-1207 - Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CIKM 2023: 1389-1399 - Xinzhou Jin, Jintang Li, Yuanzhen Xie, Liang Chen, Beibei Kong, Lei Cheng, Bo Hu, Zang Li, Zibin Zheng:
Enhancing Graph Collaborative Filtering via Neighborhood Structure Embedding. ICDM 2023: 190-199 - Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen:
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs. IJCAI 2023: 2306-2314 - Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang:
What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders. KDD 2023: 1268-1279 - Jintang Li, Sheng Tian, Ruofan Wu, Liang Zhu, Wenlong Zhao, Changhua Meng, Liang Chen, Zibin Zheng, Hongzhi Yin:
Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs. CoRR abs/2305.10673 (2023) - Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen:
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs. CoRR abs/2305.13573 (2023) - Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Liang Chen, Zibin Zheng, Baokun Wang, Changhua Meng:
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks. CoRR abs/2305.19306 (2023) - Jintang Li, Wangbin Sun, Ruofan Wu, Yuchang Zhu, Liang Chen, Zibin Zheng:
Scaling Up, Scaling Deep: Blockwise Graph Contrastive Learning. CoRR abs/2306.02117 (2023) - Yun-Cheng Wang, Jintang Xue, Chengwei Wei, C.-C. Jay Kuo:
An Overview on Generative AI at Scale with Edge-Cloud Computing. CoRR abs/2306.17170 (2023) - Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CoRR abs/2308.06801 (2023) - Jintang Xue, Yun-Cheng Wang, Chengwei Wei, Xiaofeng Liu, Jonghye Woo, C.-C. Jay Kuo:
Bias and Fairness in Chatbots: An Overview. CoRR abs/2309.08836 (2023) - Jintang Li, Zheng Wei, Jiawang Dan, Jing Zhou, Yuchang Zhu, Ruofan Wu, Baokun Wang, Zhang Zhen, Changhua Meng, Hong Jin, Zibin Zheng, Liang Chen:
Hetero$2$Net: Heterophily-aware Representation Learning on Heterogenerous Graphs. CoRR abs/2310.11664 (2023) - Jintang Li, Jiawang Dan, Ruofan Wu, Jing Zhou, Sheng Tian, Yunfei Liu, Baokun Wang, Changhua Meng, Weiqiang Wang, Yuchang Zhu, Liang Chen, Zibin Zheng:
LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning. CoRR abs/2311.16605 (2023) - Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng:
The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. CoRR abs/2311.17373 (2023) - Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
Rethinking and Simplifying Bootstrapped Graph Latents. CoRR abs/2312.02619 (2023) - 2022
- Liang Chen, Tao Xie, Jintang Li, Zibin Zheng:
Graph Enhanced Neural Interaction Model for recommendation. Knowl. Based Syst. 246: 108616 (2022) - Zhouxin Yu, Jintang Li, Liang Chen, Zibin Zheng:
Unifying multi-associations through hypergraph for bundle recommendation. Knowl. Based Syst. 255: 109755 (2022) - Zhenzhen Cheng, Yong Zhang, Waqas Muhammad, Yunhe Hao, Yujie Tang, Lili Sun, Di Wang, Jintang Zhou, Ruizhe Wang, Yuangang Deng, Yunjia Li, Li Geng, Wen Han:
Temperature Compensation With Highly Integrated Ionization Sensor Array Used in Simultaneous Detection of Mixed Gases. IEEE Trans. Ind. Electron. 69(1): 911-920 (2022) - Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo:
Spiking Graph Convolutional Networks. IJCAI 2022: 2434-2440 - Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang:
Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. KDD 2022: 4838-4839
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