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Qincheng Lu
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2020 – today
- 2024
- [c5]Ziyang Song
, Qincheng Lu
TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare. BCB 2024: 16:1-16:10 - [i11]Ziyang Song, Qincheng Lu, He Zhu, Yue Li:
Bidirectional Generative Pre-training for Improving Time Series Representation Learning. CoRR abs/2402.09558 (2024) - [i10]Qincheng Lu, Jiaqi Zhu, Sitao Luan, Xiao-Wen Chang:
Representation Learning on Heterophilic Graph with Directional Neighborhood Attention. CoRR abs/2403.01475 (2024) - [i9]Qincheng Lu, Sitao Luan, Xiao-Wen Chang:
GCEPNet: Graph Convolution-Enhanced Expectation Propagation for Massive MIMO Detection. CoRR abs/2404.14886 (2024) - [i8]Sitao Luan, Chenqing Hua, Qincheng Lu, Liheng Ma, Lirong Wu, Xinyu Wang, Minkai Xu, Xiao-Wen Chang, Doina Precup, Rex Ying, Stan Z. Li, Jian Tang, Guy Wolf, Stefanie Jegelka:
The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges. CoRR abs/2407.09618 (2024) - [i7]Sitao Luan, Qincheng Lu, Chenqing Hua, Xinyu Wang, Jiaqi Zhu, Xiao-Wen Chang, Guy Wolf, Jian Tang:
Are Heterophily-Specific GNNs and Homophily Metrics Really Effective? Evaluation Pitfalls and New Benchmarks. CoRR abs/2409.05755 (2024) - [i6]Qincheng Lu, Jiaqi Zhu, Sitao Luan, Xiao-Wen Chang:
Flexible Diffusion Scopes with Parameterized Laplacian for Heterophilic Graph Learning. CoRR abs/2409.09888 (2024) - 2023
- [c4]Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Doina Precup:
When Do We Need Graph Neural Networks for Node Classification? COMPLEX NETWORKS (1) 2023: 37-48 - [c3]Xiao-Wen Chang, Qincheng Lu, Yingzi Xu:
Success Probabilities of L2-norm Regularized Babai Detectors and Maximization. ISIT 2023: 1219-1224 - [c2]Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup:
When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability. NeurIPS 2023 - [i5]Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup:
When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability. CoRR abs/2304.14274 (2023) - [i4]Ziyang Song, Qincheng Lu, Hao Xu, Yue Li:
TimelyGPT: Recurrent Convolutional Transformer for Long Time-series Representation. CoRR abs/2312.00817 (2023) - 2022
- [c1]Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup:
Revisiting Heterophily For Graph Neural Networks. NeurIPS 2022 - [i3]Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup:
Revisiting Heterophily For Graph Neural Networks. CoRR abs/2210.07606 (2022) - [i2]Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Doina Precup:
When Do We Need GNN for Node Classification? CoRR abs/2210.16979 (2022) - 2021
- [i1]Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup:
Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? CoRR abs/2109.05641 (2021)
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