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Learning Differential Operators for Interpretable Time Series Modeling


Sep 03, 2022
Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian

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* Published in ACM SIGKDD 2022 

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Deep Stable Representation Learning on Electronic Health Records


Sep 03, 2022
Yingtao Luo, Zhaocheng Liu, Qiang Liu

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* 11 pages, 6 figures. Accepted by IEEE ICDM 2022 

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Improving Multi-Interest Network with Stable Learning


Jul 14, 2022
Zhaocheng Liu, Yingtao Luo, Di Zeng, Qiang Liu, Daqing Chang, Dongying Kong, Zhi Chen

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RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring


Jun 01, 2022
Qiang Liu, Yingtao Luo, Shu Wu, Zhen Zhang, Xiangnan Yue, Hong Jin, Liang Wang

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* Accepted by IEEE TKDE 

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AdaMCT: Adaptive Mixture of CNN-Transformer for Sequential Recommendation


May 19, 2022
Juyong Jiang, Jae Boum Kim, Yingtao Luo, Kai Zhang, Sunghun Kim

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Sequential Recommendation with Bidirectional Chronological Augmentation of Transformer


Dec 13, 2021
Juyong Jiang, Yingtao Luo, Jae Boum Kim, Kai Zhang, Sunghun Kim

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Any equation is a forest: Symbolic genetic algorithm for discovering open-form partial differential equations (SGA-PDE)


Jun 09, 2021
Yuntian Chen, Yingtao Luo, Qiang Liu, Hao Xu, Dongxiao Zhang

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* 24 pages, 16 figures 

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KO-PDE: Kernel Optimized Discovery of Partial Differential Equations with Varying Coefficients


Jun 02, 2021
Yingtao Luo, Qiang Liu, Yuntian Chen, Wenbo Hu, Jun Zhu

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* Preprint. Under review 

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STAN: Spatio-Temporal Attention Network for Next Location Recommendation


Feb 08, 2021
Yingtao Luo, Qiang Liu, Zhaocheng Liu

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* Accepted to The Web Conference (WWW2021) 

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Deep Spatial Learning with Molecular Vibration


Nov 14, 2020
Ziyang Zhang, Yingtao Luo

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* NeurIPS 2020 Machine Learning for Molecules Workshop, Vancouver, Canada 

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