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FECAM: Frequency Enhanced Channel Attention Mechanism for Time Series Forecasting


Dec 02, 2022
Maowei Jiang, Pengyu Zeng, Kai Wang, Huan Liu, Wenbo Chen, Haoran Liu

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* 11pages.10 figures,conference. arXiv admin note: text overlap with arXiv:2205.14415 by other authors 

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Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models


Oct 11, 2022
Meng Liu, Haoran Liu, Shuiwang Ji

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Learning Protein Representations via Complete 3D Graph Networks


Jul 26, 2022
Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji

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ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs


Jun 17, 2022
Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji

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Exploring the Common Principal Subspace of Deep Features in Neural Networks


Oct 06, 2021
Haoran Liu, Haoyi Xiong, Yaqing Wang, Haozhe An, Dongrui Wu, Dejing Dou

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* Main Text with Appendix, accepted by Machine Learning 

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DIG: A Turnkey Library for Diving into Graph Deep Learning Research


Mar 23, 2021
Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Zhao Xu, Haiyang Yu, Jingtun Zhang, Yi Liu, Keqiang Yan, Bora Oztekin, Haoran Liu, Xuan Zhang, Cong Fu, Shuiwang Ji

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A Blended Deep Learning Approach for Predicting User Intended Actions


Oct 11, 2018
Fei Tan, Zhi Wei, Jun He, Xiang Wu, Bo Peng, Haoran Liu, Zhenyu Yan

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* 10 pages, International Conference on Data Mining 2018 

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