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pro vyhledávání: '"Li, Shuangli"'
Finding multiple temporal relationships among locations can benefit a bunch of urban applications, such as dynamic offline advertising and smart public transport planning. While some efforts have been made on finding static relationships among locati
Externí odkaz:
http://arxiv.org/abs/2306.08921
Publikováno v:
In Journal of Manufacturing Processes 15 July 2024 121:408-426
Recently many efforts have been devoted to applying graph neural networks (GNNs) to molecular property prediction which is a fundamental task for computational drug and material discovery. One of major obstacles to hinder the successful prediction of
Externí odkaz:
http://arxiv.org/abs/2109.11730
Autor:
Li, Shuangli, Zhou, Jingbo, Xu, Tong, Huang, Liang, Wang, Fan, Xiong, Haoyi, Huang, Weili, Dou, Dejing, Xiong, Hui
Drug discovery often relies on the successful prediction of protein-ligand binding affinity. Recent advances have shown great promise in applying graph neural networks (GNNs) for better affinity prediction by learning the representations of protein-l
Externí odkaz:
http://arxiv.org/abs/2107.10670
Publikováno v:
In Science of the Total Environment 1 March 2024 914
Autor:
Luo, Hui, Zhou, Jingbo, Bao, Zhifeng, Li, Shuangli, Culpepper, J. Shane, Ying, Haochao, Liu, Hao, Xiong, Hui
Publikováno v:
SIGIR Conference (2020) 781-790
Existing spatial object recommendation algorithms generally treat objects identically when ranking them. However, spatial objects often cover different levels of spatial granularity and thereby are heterogeneous. For example, one user may prefer to b
Externí odkaz:
http://arxiv.org/abs/2101.02969
Autor:
Zhou, Jingbo, Li, Shuangli, Huang, Liang, Xiong, Haoyi, Wang, Fan, Xu, Tong, Xiong, Hui, Dou, Dejing
Accurately predicting the binding affinity between drugs and proteins is an essential step for computational drug discovery. Since graph neural networks (GNNs) have demonstrated remarkable success in various graph-related tasks, GNNs have been consid
Externí odkaz:
http://arxiv.org/abs/2012.09624
Akademický článek
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Akademický článek
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Publikováno v:
In Journal of Water Process Engineering July 2023 53