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Wei Jin
Wei Jin
Assistant Professor, Emory University
Verifisert e-postadresse på emory.edu - Startside
Tittel
Sitert av
Sitert av
År
Graph Structure Learning for Robust Graph Neural Networks
W Jin, Y Ma, X Liu, X Tang, S Wang, J Tang
KDD 2020, 2020
7432020
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
6062020
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
316*2021
Exploring the potential of large language models (llms) in learning on graphs
Z Chen, H Mao, H Li, W Jin, H Wen, X Wei, S Wang, D Yin, W Fan, H Liu, ...
SIGKDD Explorations, 2023
2982023
Node Similarity Preserving Graph Convolutional Networks
W Jin, T Derr, Y Wang, Y Ma, Z Liu, J Tang
International Conference on Web Search and Data Mining (WSDM), 2021
2812021
Self-supervised learning on graphs: Deep insights and new direction
W Jin, T Derr, H Liu, Y Wang, S Wang, Z Liu, J Tang
The Web Conference (WWW 2021) Workshop: Self-Supervised Learning for the Web, 2021
2442021
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness
L Zhao, W Jin, L Akoglu, N Shah
International Conference on Learning Representations (ICLR), 2022
1962022
Graph Condensation for Graph Neural Networks
W Jin, L Zhao, S Zhang, Y Liu, J Tang, N Shah
International Conference on Learning Representations (ICLR), 2022
1822022
Deeprobust: A pytorch library for adversarial attacks and defenses
Y Li*, W Jin*, H Xu, J Tang
arXiv preprint arXiv:2005.06149, 2020
1632020
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 (ICML), 6837-6849, 2021
1452021
Graph Data Augmentation for Graph Machine Learning: A Survey
T Zhao, W Jin, Y Wang, G Liu, Y Liu, S Gunnemann, N Shah, M Jiang
IEEE Data Engineering Bulletin (DEBULL), 2023
1272023
Graph trend filtering networks for recommendation
W Fan, X Liu, W Jin, X Zhao, J Tang, Q Li
Proceedings of the 45th international ACM SIGIR conference on research and …, 2022
1192022
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels
E Dai, W Jin, H Liu, S Wang
WSDM 2022, 2022
1112022
Condensing Graphs via One-Step Gradient Matching
W Jin, X Tang, H Jiang, Z Li, D Zhang, J Tang, B Yin
KDD 2022, 2022
1072022
Automated self-supervised learning for graphs
W Jin, X Liu, X Zhao, Y Ma, N Shah, J Tang
International Conference on Learning Representations (ICLR), 2022
902022
Graph neural networks with adaptive residual
X Liu, J Ding, W Jin, H Xu, Y Ma, Z Liu, J Tang
NeurIPS 2021, 2021
812021
Empowering graph representation learning with test-time graph transformation
W Jin, T Zhao, J Ding, Y Liu, J Tang, N Shah
ICLR 2023, 2022
712022
Graph Neural Networks for Multimodal Single-Cell Data Integration
H Wen*, J Ding*, W Jin*, Y Wang*, Y Xie, J Tang
KDD 2022, 2022
702022
Label-free node classification on graphs with large language models (llms)
Z Chen, H Mao, H Wen, H Han, W Jin, H Zhang, H Liu, J Tang
ICLR 2024, 2024
662024
Demystifying structural disparity in graph neural networks: Can one size fit all?
H Mao, Z Chen, W Jin, H Han, Y Ma, T Zhao, N Shah, J Tang
Advances in neural information processing systems 36, 37013-37067, 2023
602023
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