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Wu, Qitian
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1

ScaleGCN: Efficient and Effective Graph Convolution via Cha..:

Zhang, Tianqi ; Wu, Qitian ; Yan, Junchi..
IEEE Transactions on Neural Networks and Learning Systems.  35 (2024)  4 - p. 4478-4490 , 2024
Link: https://doi.org/10.1109/..
 
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2

Graph Out-of-Distribution Generalization via Causal Interve..:

, In: Proceedings of the ACM on Web Conference 2024,
Wu, Qitian ; Nie, Fan ; Yang, Chenxiao.. - p. 850-860 , 2024
Link: https://dl.acm.org/doi/1..
 
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3

Rethinking Cross-Domain Sequential Recommendation under Ope..:

, In: Proceedings of the ACM on Web Conference 2024,
Xu, Wujiang ; Wu, Qitian ; Wang, Runzhong... - p. 3173-3184 , 2024
Link: https://dl.acm.org/doi/1..
 
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4

MoleRec: Combinatorial Drug Recommendation with Substructur..:

, In: Proceedings of the ACM Web Conference 2023,
Yang, Nianzu ; Zeng, Kaipeng ; Wu, Qitian. - p. 4075-4085 , 2023
Link: https://dl.acm.org/doi/1..
 
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5

GraphGLOW: Universal and Generalizable Structure Learning f..:

, In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,
Zhao, Wentao ; Wu, Qitian ; Yang, Chenxiao. - p. 3525-3536 , 2023
Link: https://dl.acm.org/doi/1..
 
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6

Learning High-Order Graph Convolutional Networks via Adapti..:

Zhang, Tianqi ; Wu, Qitian ; Yan, Junchi
IEEE Transactions on Neural Networks and Learning Systems.  34 (2023)  8 - p. 5144-5155 , 2023
Link: https://doi.org/10.1109/..
 
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7

DICE: Domain-attack Invariant Causal Learning for Improved ..:

, In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,
Ren, Qibing ; Chen, Yiting ; Mo, Yichuan.. - p. 1483-1492 , 2022
Link: https://dl.acm.org/doi/1..
 
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8

Variational Inference for Training Graph Neural Networks in..:

, In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,
Lao, Danning ; Yang, Xinyu ; Wu, Qitian. - p. 824-834 , 2022
Link: https://dl.acm.org/doi/1..
 
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9

Seq2Bubbles : Region-Based Embedding Learning for User B..:

, In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management,
Wu, Qitian ; Yang, Chenxiao ; Yu, Shuodian.. - p. 2160-2169 , 2021
Link: https://dl.acm.org/doi/1..
 
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10

SentiMem: Attentive Memory Networks for Sentiment Classific..:

, In: Database Systems for Advanced Applications; Lecture Notes in Computer Science,
Jia, Xiaosong ; Wu, Qitian ; Gao, Xiaofeng. - p. 736-751 , 2020
Link: https://doi.org/10.1007/..
 
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11

Dual Graph Attention Networks for Deep Latent Representatio..:

, In: The World Wide Web Conference,
Wu, Qitian ; Zhang, Hengrui ; Gao, Xiaofeng... - p. 2091-2102 , 2019
Link: https://dl.acm.org/doi/1..
 
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12

Dual Sequential Prediction Models Linking Sequential Recomm..:

, In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,
Wu, Qitian ; Gao, Yirui ; Gao, Xiaofeng.. - p. 447-457 , 2019
Link: https://dl.acm.org/doi/1..
 
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13

Adversarial Training Model Unifying Feature Driven and Poin..:

, In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management,
Wu, Qitian ; Yang, Chaoqi ; Zhang, Hengrui... - p. 517-526 , 2018
Link: https://dl.acm.org/doi/1..
 
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14

EPOC: A Survival Perspective Early Pattern Detection Model ..:

, In: Lecture Notes in Computer Science; Database and Expert Systems Applications,
Yang, Chaoqi ; Wu, Qitian ; Gao, Xiaofeng. - p. 336-351 , 2018
Link: https://doi.org/10.1007/..
 
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15

GraphGLOW: Universal and Generalizable Structure Learning f..:

Zhao, Wentao ; Wu, Qitian ; Yang, Chenxiao.
http://arxiv.org/abs/2306.11264.  , 2023
Link: http://arxiv.org/abs/230..
 
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