フォロー
Qitian Wu
タイトル
引用先
引用先
Dual graph attention networks for deep latent representation of multifaceted social effects in recommender systems
Q Wu, H Zhang, X Gao, P He, P Weng, H Gao, G Chen
The Web Conference (WWW, Oral), 2019
3252019
From canonical correlation analysis to self-supervised graph neural networks
H Zhang, Q Wu, J Yan, D Wipf, SY Philip
Advances in Neural Information Processing Systems (NeurIPS), 2021
1582021
Handling distribution shifts on graphs: An invariance perspective
Q Wu, H Zhang, J Yan, D Wipf
International Conference on Learning Representations (ICLR), 2022
1372022
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification
Q Wu, W Zhao, Z Li, D Wipf, J Yan
Advances in Neural Information Processing Systems (NeurIPS, Spotlight), 2022
1192022
Dual sequential prediction models linking sequential recommendation and information dissemination
Q Wu, Y Gao, X Gao, P Weng, G Chen
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019
78*2019
Learning Substructure Invariance for Out-of-Distribution Molecular Representations
N Yang, K Zeng, Q Wu, X Jia, J Yan
Advances in Neural Information Processing Systems (NeurIPS, Spotlight), 2022
622022
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
Q Wu, C Yang, W Zhao, Y He, D Wipf, J Yan
International Conference on Learning Representations (ICLR, Spotlight), 2023
462023
Towards open-world recommendation: An inductive model-based collaborative filtering approach
Q Wu, H Zhang, X Gao, J Yan, H Zha
International Conference on Machine Learning (ICML), 2021
422021
Energy-based Out-of-Distribution Detection for Graph Neural Networks
Q Wu, Y Chen, C Yang, J Yan
International Conference on Learning Representations (ICLR), 2023
412023
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs
C Yang, Q Wu, J Wang, J Yan
International Conference on Learning Representations (ICLR), 2023
402023
GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs
Z Li, Q Wu, F Nie, J Yan
Advances in Neural Information Processing Systems (NeurIPS), 2022
262022
Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach
Q Wu, C Yang, J Yan
Advances in Neural Information Processing Systems (NeurIPS), 2021
262021
Adversarial training model unifying feature driven and point process perspectives for event popularity prediction
Q Wu, C Yang, H Zhang, X Gao, P Weng, G Chen
ACM International Conference on Information and Knowledge Management (CIKM), 2018
242018
Molerec: Combinatorial drug recommendation with substructure-aware molecular representation learning
N Yang, K Zeng, Q Wu, J Yan
The Web Conference (WWW), 2023
222023
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks
C Yang, Q Wu, J Yan
Advances in Neural Information Processing Systems (NeurIPS), 2022
202022
Feature Evolution Based Multi-Task Learning for Collaborative Filtering with Social Trust.
Q Wu, L Jiang, X Gao, X Yang, G Chen
International Joint Conference on Artificial Intelligence (IJCAI), 2019
182019
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment
C Yang, Q Wu, Q Wen, Z Zhou, L Sun, J Yan
Advances in Neural Information Processing Systems (NeurIPS), 2022
162022
Variational inference for training graph neural networks in low-data regime through joint structure-label estimation
D Lao, X Yang, Q Wu, J Yan
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022
162022
Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach
C Yang, Q Wu, J Jin, X Gao, J Pan, G Chen
International Joint Conference on Artificial Intelligence (IJCAI), 2022
152022
SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations
Q Wu, W Zhao, C Yang, H Zhang, F Nie, H Jiang, Y Bian, J Yan
Advances in Neural Information Processing Systems (NeurIPS), 2023
14*2023
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