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Jintang Li
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2020 – today
- 2024
- [c18]Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen:
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks. ICLR 2024 - [c17]Yunfei Liu
, Jintang Li
, Yuehe Chen
, Ruofan Wu
, Ericbk Wang
, Jing Zhou
, Sheng Tian
, Shuheng Shen
, Xing Fu
, Changhua Meng
, Weiqiang Wang
, Liang Chen
:
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. KDD 2024: 1968-1979 - [c16]Yuchang Zhu
, Jintang Li
, Yatao Bian
, Zibin Zheng
, Liang Chen
:
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. KDD 2024: 4688-4699 - [c15]Zulun Zhu
, Kai Wang
, Haoyu Liu
, Jintang Li
, Siqiang Luo
:
Topology-monitorable Contrastive Learning on Dynamic Graphs. KDD 2024: 4700-4711 - [c14]Wangbin Sun
, Jintang Li
, Liang Chen
, Bingzhe Wu
, Yatao Bian
, Zibin Zheng
:
Rethinking and Simplifying Bootstrapped Graph Latents. WSDM 2024: 665-673 - [c13]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 - [c12]Yuchang Zhu
, Jintang Li
, Zibin Zheng
, Liang Chen
:
Fair Graph Representation Learning via Sensitive Attribute Disentanglement. WWW 2024: 1182-1192 - [i28]Huizhe Zhang, Jintang Li, Liang Chen, Zibin Zheng:
SGHormer: An Energy-Saving Graph Transformer Driven by Spikes. CoRR abs/2403.17656 (2024) - [i27]Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen:
Fair Graph Representation Learning via Sensitive Attribute Disentanglement. CoRR abs/2405.07011 (2024) - [i26]Jintang Li, Ruofan Wu, Xinzhou Jin, Boqun Ma, Liang Chen, Zibin Zheng:
State Space Models on Temporal Graphs: A First-Principles Study. CoRR abs/2406.00943 (2024) - [i25]Yuchang Zhu, Jintang Li, Yatao Bian
, Zibin Zheng, Liang Chen:
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. CoRR abs/2406.13544 (2024) - [i24]Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen:
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. CoRR abs/2406.14288 (2024) - [i23]Xinzhou Jin, Jintang Li, Liang Chen, Chenyun Yu, Yuanzhen Xie, Tao Xie, Chengxiang Zhuo, Zang Li, Zibin Zheng:
L2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering. CoRR abs/2407.14266 (2024) - 2023
- [j5]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) - [j4]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) - [c11]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 - [c10]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 - [c9]Jie Liao
, Jintang Li
, Liang Chen
, Bingzhe Wu
, Yatao Bian
, Zibin Zheng
:
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CIKM 2023: 1389-1399 - [c8]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 - [c7]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 - [c6]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 - [i22]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) - [i21]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) - [i20]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) - [i19]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) - [i18]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) - [i17]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) - [i16]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) - [i15]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) - [i14]Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian
, Zibin Zheng:
Rethinking and Simplifying Bootstrapped Graph Latents. CoRR abs/2312.02619 (2023) - 2022
- [j3]Liang Chen, Tao Xie, Jintang Li, Zibin Zheng:
Graph Enhanced Neural Interaction Model for recommendation. Knowl. Based Syst. 246: 108616 (2022) - [j2]Zhouxin Yu
, Jintang Li
, Liang Chen, Zibin Zheng:
Unifying multi-associations through hypergraph for bundle recommendation. Knowl. Based Syst. 255: 109755 (2022) - [c5]Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu
, Siqiang Luo:
Spiking Graph Convolutional Networks. IJCAI 2022: 2434-2440 - [c4]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 - [i13]Liang Chen, Qibiao Peng, Jintang Li, Yang Liu, Jiawei Chen, Yong Li, Zibin Zheng:
Neighboring Backdoor Attacks on Graph Convolutional Network. CoRR abs/2201.06202 (2022) - [i12]Bingzhe Wu, Jintang Li, Chengbin Hou, Guoji Fu, Yatao Bian, Liang Chen, Junzhou Huang:
Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift. CoRR abs/2202.07114 (2022) - [i11]Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Changhua Meng, Zibin Zheng, Weiqiang Wang:
GUARD: Graph Universal Adversarial Defense. CoRR abs/2204.09803 (2022) - [i10]Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu
, Siqiang Luo
:
Spiking Graph Convolutional Networks. CoRR abs/2205.02767 (2022) - [i9]Bingzhe Wu, Jintang Li, Junchi Yu, Yatao Bian
, Hengtong Zhang, Chaochao Chen, Chengbin Hou
, Guoji Fu, Liang Chen, Tingyang Xu
, Yu Rong, Xiaolin Zheng, Junzhou Huang
, Ran He, Baoyuan Wu, Guangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao:
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. CoRR abs/2205.10014 (2022) - [i8]Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang:
MaskGAE: Masked Graph Modeling Meets Graph Autoencoders. CoRR abs/2205.10053 (2022) - [i7]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. CoRR abs/2208.10364 (2022) - [i6]Zishan Gu, Jintang Li, Liang Chen:
Are All Edges Necessary? A Unified Framework for Graph Purification. CoRR abs/2211.05184 (2022) - [i5]Jintang Li, Jiaying Peng, Liang Chen, Zibin Zheng, Tingting Liang, Qing Ling:
Spectral Adversarial Training for Robust Graph Neural Network. CoRR abs/2211.10896 (2022) - 2021
- [j1]Liang Chen, Jiaying Peng, Yang Liu
, Jintang Li, Fenfang Xie, Zibin Zheng
:
Phishing Scams Detection in Ethereum Transaction Network. ACM Trans. Internet Techn. 21(1): 10:1-10:16 (2021) - [c3]Jintang Li, Kun Xu, Liang Chen, Zibin Zheng
, Xiao Liu:
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software. ICSE (Companion Volume) 2021: 13-16 - [c2]Liang Chen, Jintang Li, Qibiao Peng, Yang Liu
, Zibin Zheng, Carl Yang:
Understanding Structural Vulnerability in Graph Convolutional Networks. IJCAI 2021: 2249-2255 - [i4]Jintang Li, Kun Xu, Liang Chen, Zibin Zheng, Xiao Liu:
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software. CoRR abs/2102.07933 (2021) - [i3]Liang Chen, Jintang Li, Qibiao Peng, Yang Liu, Zibin Zheng, Carl Yang:
Understanding Structural Vulnerability in Graph Convolutional Networks. CoRR abs/2108.06280 (2021) - 2020
- [c1]Jintang Li, Zishan Gu, Qibiao Peng, Kun Xu, Liang Chen, Zibin Zheng
:
Deep Insights into Graph Adversarial Learning: An Empirical Study Perspective. HBAI@IJCAI 2020: 87-101 - [i2]Liang Chen, Jintang Li, Jiaying Peng, Tao Xie, Zengxu Cao, Kun Xu, Xiangnan He, Zibin Zheng:
A Survey of Adversarial Learning on Graphs. CoRR abs/2003.05730 (2020) - [i1]Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng:
Adversarial Attack on Large Scale Graph. CoRR abs/2009.03488 (2020)
Coauthor Index
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last updated on 2024-09-10 02:07 CEST by the dblp team
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