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of 55
pro vyhledávání: '"Wen, Yanlong"'
Autor:
Zhou, Xinxing, Ye, Jiaqi, Zhao, Shubao, Jin, Ming, Hou, Zhaoxiang, Yang, Chengyi, Li, Zengxiang, Wen, Yanlong, Yuan, Xiaojie
In the context of global energy strategy, accurate natural gas demand forecasting is crucial for ensuring efficient resource allocation and operational planning. Traditional forecasting methods struggle to cope with the growing complexity and variabi
Externí odkaz:
http://arxiv.org/abs/2409.15794
Graph representation learning (GRL) models have succeeded in many scenarios. Real-world graphs have imbalanced distribution, such as node labels and degrees, which leaves a critical challenge to GRL. Imbalanced inputs can lead to imbalanced outputs.
Externí odkaz:
http://arxiv.org/abs/2409.05339
Graph Transformers (GTs) have made remarkable achievements in graph-level tasks. However, most existing works regard graph structures as a form of guidance or bias for enhancing node representations, which focuses on node-central perspectives and lac
Externí odkaz:
http://arxiv.org/abs/2404.11869
ICD coding is designed to assign the disease codes to electronic health records (EHRs) upon discharge, which is crucial for billing and clinical statistics. In an attempt to improve the effectiveness and efficiency of manual coding, many methods have
Externí odkaz:
http://arxiv.org/abs/2305.18576
Akademický článek
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Autor:
Su, Rongzhen, Wen, Yanlong, Prabakusuma, Adhita Sri, Tang, Xiaozhao, Huang, Aixiang, Li, Lingfei
Publikováno v:
In International Dairy Journal September 2023 144
Publikováno v:
In Expert Systems With Applications 1 June 2023 219
Publikováno v:
In Big Data Research 28 November 2022 30
Autor:
Zhang, Jiaming1 (AUTHOR), Wen, Yanlong1 (AUTHOR), Han, Meina1 (AUTHOR), Zhang, Letian1 (AUTHOR), Liu, Shihao1 (AUTHOR) liushihao@jlu.edu.cn, Xie, Wenfa1 (AUTHOR) xiewf@jlu.edu.cn, Yu, Cunjiang2,3,4 (AUTHOR) cmy5358@psu.edu
Publikováno v:
Laser & Photonics Reviews. Oct2024, p1. 9p. 6 Illustrations.
Publikováno v:
IEEE Transactions on Industrial Informatics. 18:3562-3571
The federated learning provides an effective solution to train collaborative models over a large scale of participated Industrial Internet of Things (IIoT) applications with the help of a global server, building an intelligent life. However, the fede
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cfec6fcc25f03aab2df18abcc285faa
https://doi.org/10.1109/tii.2021.3112100
https://doi.org/10.1109/tii.2021.3112100