Zemin Liu

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Yuan FANGAssistant Professor, School of Computing and Information Systems, Singapore Management UniversityDirección de correo verificada de smu.edu.sg
Chenghao LiuSalesforce Research AsiaDirección de correo verificada de salesforce.com
Minghui WuZhejiang University City CollegeDirección de correo verificada de zucc.edu.cn
Vincent W. ZhengADSC, SingaporeDirección de correo verificada de adsc.com.sg
Steven C.H. HoiManaging Director of Salesforce Research Asia; IEEE Fellow; Professor at SMUDirección de correo verificada de smu.edu.sg
Kevin Chen-Chuan ChangUniversity of Illinois at Urbana-ChampaignDirección de correo verificada de illinois.edu
Zhou ZhaoZhejiang UniversityDirección de correo verificada de zju.edu.cn
Bingsheng He, 何丙胜Professor, Department of Computer Science, National University of SingaporeDirección de correo verificada de comp.nus.edu.sg
Jia WangFacebookDirección de correo verificada de meta.com
Bryan HooiNational University of SingaporeDirección de correo verificada de comp.nus.edu.sg
Xiangnan HeUniversity of Science and Technology of China, School of Data ScienceDirección de correo verificada de ustc.edu.cn
Xiang WangUniversity of Science and Technology of ChinaDirección de correo verificada de ustc.edu.cn
Wu MinPrincipal Scientist, Institute for Infocomm ResearchDirección de correo verificada de i2r.a-star.edu.sg
Yong LiuHuawei, NTU, I2RDirección de correo verificada de huawei.com
Fei WuProfessor of Computer Science, Zhejiang UniversityDirección de correo verificada de cs.zju.edu.cn
Junchi YanFIAPR/FIET/IEEE-AI2Watch, Prof. SJTU (2018-), SII (2024-), IBM (2011-2018)Dirección de correo verificada de cs.sjtu.edu.cn

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Zemin Liu

Zhejiang University

Dirección de correo verificada de zju.edu.cn - Página principal

Graph Learning Graph Imbalanced Learning


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Topological recurrent neural network for diffusion prediction J Wang, VW Zheng, Z Liu, KCC Chang Proceedings of The IEEE International Conference on Data Mining (ICDM), 2017	194	2017
Graphprompt: Unifying pre-training and downstream tasks for graph neural networks Z Liu, X Yu, Y Fang, X Zhang Proceedings of the ACM Web Conference 2023, 417-428, 2023	165	2023
Tail-GNN: Tail-node graph neural networks Z Liu, TK Nguyen, Y Fang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021	122	2021
Relative and absolute location embedding for few-shot node classification on graph Z Liu, Y Fang, C Liu, SCH Hoi Proceedings of the AAAI conference on artificial intelligence 35 (5), 4267-4275, 2021	91	2021
Semantic proximity search on heterogeneous graph by proximity embedding Z Liu, VW Zheng, Z Zhao, F Zhu, KCC Chang, M Wu, J Ying Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017	88	2017
Towards locality-aware meta-learning of tail node embeddings on networks Z Liu, W Zhang, Y Fang, X Zhang, SCH Hoi Proceedings of the 29th ACM International Conference on Information …, 2020	60	2020
mg2vec: Learning relationship-preserving heterogeneous graph representations via metagraph embedding W Zhang, Y Fang, Z Liu, M Wu, X Zhang IEEE Transactions on Knowledge and Data Engineering 34 (3), 1317-1329, 2020	59	2020
Hinormer: Representation learning on heterogeneous information networks with graph transformer Q Mao, Z Liu, C Liu, J Sun Proceedings of the ACM Web Conference 2023, 599-610, 2023	56	2023
Distance-aware dag embedding for proximity search on heterogeneous graphs Z Liu, V Zheng, Z Zhao, F Zhu, K Chang, M Wu, J Ying Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	43	2018
Interactive paths embedding for semantic proximity search on heterogeneous graphs Z Liu, VW Zheng, Z Zhao, Z Li, H Yang, M Wu, J Ying Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	41	2018
Meta-inductive node classification across graphs Z Wen, Y Fang, Z Liu Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021	37	2021
On Generalized Degree Fairness in Graph Neural Networks Z Liu, TK Nguyen, Y Fang Proceedings of the AAAI Conference on Artificial Intelligence 37 (1), 2023	36	2023
Subgraph-augmented path embedding for semantic user search on heterogeneous social network Z Liu, VW Zheng, Z Zhao, H Yang, KCC Chang, M Wu, J Ying Proceedings of the 2018 World Wide Web Conference, 1613-1622, 2018	33	2018
Hgprompt: Bridging homogeneous and heterogeneous graphs for few-shot prompt learning X Yu, Y Fang, Z Liu, X Zhang Proceedings of the AAAI Conference on Artificial Intelligence 38 (15), 16578 …, 2024	30	2024
Cooperative Explanations of Graph Neural Networks J Fang, X Wang, A Zhang, Z Liu, X He, TS Chua Proceedings of the 16th ACM International Conference on Web Search and Data …, 2023	29	2023
Evaluating post-hoc explanations for graph neural networks via robustness analysis J Fang, W Liu, Y Gao, Z Liu, A Zhang, X Wang, X He Advances in Neural Information Processing Systems 36, 2024	27	2024
Node-wise localization of graph neural networks Z Liu, Y Fang, C Liu, SCH Hoi International Joint Conferences on Artificial Intelligence, 2021	27	2021
Learning to count isomorphisms with graph neural networks X Yu, Z Liu, Y Fang, X Zhang Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 4845-4853, 2023	23	2023
On size-oriented long-tailed graph classification of graph neural networks Z Liu, Q Mao, C Liu, Y Fang, J Sun Proceedings of the ACM Web Conference 2022, 1506-1516, 2022	21	2022
Generalized graph prompt: Toward a unification of pre-training and downstream tasks on graphs X Yu, Z Liu, Y Fang, Z Liu, S Chen, X Zhang IEEE Transactions on Knowledge and Data Engineering, 2024	20	2024

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