Yiqi Wang
Cited by
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Traffic flow prediction via spatial temporal graph neural network
X Wang, Y Ma, Y Wang, W Jin, X Wang, J Tang, C Jia, J Yu
Proceedings of the web conference 2020, 1082-1092, 2020
Node similarity preserving graph convolutional networks
W Jin, T Derr, Y Wang, Y Ma, Z Liu, J Tang
Proceedings of the 14th ACM international conference on web search and data …, 2021
Self-supervised learning on graphs: Deep insights and new direction
W Jin, T Derr, H Liu, Y Wang, S Wang, Z Liu, J Tang
arXiv preprint arXiv:2006.10141, 2020
Adversarial attacks and defenses on graphs: A review and empirical study
W Jin, Y Li, H Xu, Y Wang, J Tang
arXiv preprint arXiv:2003.00653 10 (3447556.3447566), 2020
Adversarial attacks and defenses on graphs
W Jin, Y Li, H Xu, Y Wang, S Ji, C Aggarwal, J Tang
ACM SIGKDD Explorations Newsletter 22 (2), 19-34, 2021
Trustworthy ai: A computational perspective
H Liu, Y Wang, W Fan, X Liu, Y Li, S Jain, Y Liu, A Jain, J Tang
ACM Transactions on Intelligent Systems and Technology 14 (1), 1-59, 2022
Elastic graph neural networks
X Liu, W Jin, Y Ma, Y Li, H Liu, Y Wang, M Yan, J Tang
International Conference on Machine Learning, 6837-6849, 2021
Investigating and mitigating degree-related biases in graph convoltuional networks
X Tang, H Yao, Y Sun, Y Wang, J Tang, C Aggarwal, P Mitra, S Wang
Proceedings of the 29th ACM International Conference on Information …, 2020
Mitigating gender bias for neural dialogue generation with adversarial learning
H Liu, W Wang, Y Wang, H Liu, Z Liu, J Tang
arXiv preprint arXiv:2009.13028, 2020
Deep graph learning: Foundations, advances and applications
Y Rong, T Xu, J Huang, W Huang, H Cheng, Y Ma, Y Wang, T Derr, L Wu, ...
Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020
Graph neural networks for multimodal single-cell data integration
H Wen, J Ding, W Jin, Y Wang, Y Xie, J Tang
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
Gophormer: Ego-Graph Transformer for Node Classification
J Zhao, C Li, Q Wen, Y Wang, Y Liu, H Sun, X Xie, Y Ye
arXiv preprint arXiv:2110.13094, 2021
Graph pooling with representativeness
J Li, Y Ma, Y Wang, C Aggarwal, CD Wang, J Tang
2020 IEEE International Conference on Data Mining (ICDM), 302-311, 2020
Deep embedding for determining the number of clusters
Y Wang, Z Shi, X Guo, X Liu, E Zhu, J Yin
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
GT-WGS: an efficient and economic tool for large-scale WGS analyses based on the AWS cloud service
Y Wang, G Li, M Ma, F He, Z Song, W Zhang, C Wu
BMC genomics 19, 89-98, 2018
House: Knowledge graph embedding with householder parameterization
R Li, J Zhao, C Li, D He, Y Wang, Y Liu, H Sun, S Wang, W Deng, Y Shen, ...
International Conference on Machine Learning, 13209-13224, 2022
Localized Graph Collaborative Filtering
Y Wang, C Li, M Li, W Jin, Y Liu, H Sun, X Xie, J Tang
arXiv preprint arXiv:2108.04475, 2021
A Comprehensive Survey on Trustworthy Recommender Systems
W Fan, X Zhao, X Chen, J Su, J Gao, L Wang, Q Liu, Y Wang, H Xu, ...
arXiv preprint arXiv:2209.10117, 2022
An Adaptive Graph Pre-training Framework for Localized Collaborative Filtering
Y Wang, C Li, Z Liu, M Li, J Tang, X Xie, L Chen, PS Yu
ArXiv Preprint arXiv:2112.07191, 2021
Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?
J Li, H Shomer, J Ding, Y Wang, Y Ma, N Shah, J Tang, D Yin
arXiv preprint arXiv:2205.10652, 2022
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