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Kun Wang
Kun Wang
Ph.D. candidate @ USTC| Data Science @ NUS @Squirrel AI @ NTU
Verified email at mail.ustc.edu.cn - Homepage
Title
Cited by
Cited by
Year
Deciphering spatio-temporal graph forecasting: A causal lens and treatment
Y Xia, Y Liang, H Wen, X Liu, K Wang, Z Zhou, R Zimmermann
Conference on Neural Information Processing Systems (Neurips 2023), 2023
382023
Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
K Wang, Y Liang, P Wang, X Wang, P Gu, J Fang, Y Wang
The Eleventh International Conference on Learning Representations (ICLR 2023), 2022
302022
Practical synthetic human trajectories generation based on variational point processes
Q Long, H Wang, T Li, L Huang, K Wang, Q Wu, G Li, Y Liang, L Yu, Y Li
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
272023
Brave the Wind and the Waves: Discovering Robust and Generalizable Graph Lottery Tickets
K Wang, Y Liang, X Li, G Li, B Ghanem, R Zimmermann, H Yi, Y Zhang, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI 2023), 2023
252023
Maintaining the Status Quo: Capturing Invariant Relations for OOD Spatiotemporal Learning
Z Zhou, Q Huang, K Yang, K Wang, X Wang, Y Zhang, Y Liang, Y Wang
KDD 2023, 2023
252023
Earthfarseer: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model
H Wu, S Wang, Y Liang, Z Zhou, W Huang, W Xiong, K Wang
(* corresponding author) AAAI 2024, 2024
242024
Exgc: Bridging efficiency and explainability in graph condensation
J Fang, X Li, Y Sui, Y Gao, G Zhang, K Wang, X Wang, X He
(corresponding author) WWW 2024, 2024
212024
The Snowflake Hypothesis: Training and Powering GNN with One Node One Receptive Field
K Wang, G Li, S Wang, G Zhang, K Wang, Y You, J Fang, X Peng, Y Liang, ...
KDD 2024, 3152-3163, 2024
17*2024
Moltc: Towards molecular relational modeling in language models
J Fang, S Zhang, C Wu, Z Yang, Z Liu, S Li, K Wang, W Du, X Wang
arXiv preprint arXiv:2402.03781, 2024
162024
Modeling spatio-temporal dynamical systems with neural discrete learning and levels-of-experts
K Wang, H Wu, G Zhang, J Fang, Y Liang, Y Wu, R Zimmermann, Y Wang
IEEE Transactions on Knowledge and Data Engineering, 2024
132024
Graph Lottery Ticket Automated
G Zhang, K Wang, W Huang, Y Yue, Y Wang, R Zimmermann, A Zhou, ...
ICLR 2024 (Equal Contribution), 2023
132023
MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?
YF Zhang, H Zhang, H Tian, C Fu, S Zhang, J Wu, F Li, K Wang, Q Wen, ...
arXiv preprint arXiv:2408.13257 (benchmark research), 2024
112024
Attend who is weak: Enhancing graph condensation via cross-free adversarial training
X Li, K Wang, H Deng, Y Liang, D Wu
(* Corresponding author) arXiv preprint arXiv:2311.15772, 2023
112023
Two heads are better than one: Boosting graph sparse training via semantic and topological awareness
G Zhang, Y Yue, K Wang, J Fang, Y Sui, K Wang, Y Liang, D Cheng, ...
arXiv preprint arXiv:2402.01242 (ICML 2024 Corresponding author), 2024
102024
On regularization for explaining graph neural networks: An information theory perspective
J Fang, G Zhang, K Wang, W Du, Y Duan, Y Wu, R Zimmermann, X Chu, ...
IEEE TKDE 2024 (*Corresponding author), 2023
102023
A2DJP: A two graph-based component fused learning framework for urban anomaly distribution and duration joint-prediction
K Wang, Z Zhou, X Wang, P Wang, Q Fang, Y Wang
IEEE Transactions on Knowledge and Data Engineering (TKDE 2022), 2022
102022
CaT-GNN: Enhancing Credit Card Fraud Detection via Causal Temporal Graph Neural Networks
Y Duan, G Zhang, S Wang, X Peng, W Ziqi, J Mao, H Wu, X Jiang, K Wang
(Corresponding author *) arXiv preprint arXiv:2402.14708, 2024
92024
Two trades is not baffled: Condense graph via crafting rational gradient matching
T Zhang, Y Zhang, K Wang, K Wang, B Yang, K Zhang, W Shao, P Liu, ...
arXiv preprint arXiv:2402.04924, 2024
92024
Graph neural networks in EEG-based emotion recognition: a survey
C Liu, X Zhou, Y Wu, R Yang, Z Wang, L Zhai, Z Jia, Y Liu
arXiv preprint arXiv:2402.01138, 2024
92024
UrbanVLP: A Multi-Granularity Vision-Language Pre-Trained Foundation Model for Urban Indicator Prediction
X Hao, W Chen, Y Yan, S Zhong, K Wang, Q Wen, Y Liang
arXiv preprint arXiv:2403.16831, 2024
72024
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