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DyFiLM: A framework to handle the distribution shifts on dynamic graphs with hypernetworks.

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第一作者： Fuyuan,Ma

第一单位： College of Artificial Intelligence, Jilin University, Changchun, Jilin Province, 130012, China. Electronic address: mafy23@mails.jlu.edu.cn.

作者： Fuyuan,Ma ^[1] ; Yuhan,Wang ^[2] ; Shixuan,Ma ^[3] ; Yongzhen,Li ^[3] ; Xin,Wang ^[4] ; Ying,Wang ^[5]

作者单位： College of Artificial Intelligence, Jilin University, Changchun, Jilin Province, 130012, China. Electronic address: mafy23@mails.jlu.edu.cn. ^[1] College of Software, Jilin University, Changchun, Jilin Province, 130012, China. ^[2] College of Computer Science and Technology, Jilin University, Changchun, Jilin Province, 130012, China. ^[3] College of Artificial Intelligence, Jilin University, Changchun, Jilin Province, 130012, China. Electronic address: xinwang@jlu.edu.cn. ^[4] College of Computer Science and Technology, Jilin University, Changchun, Jilin Province, 130012, China; Key Laboratory of Symbol Computation and Knowledge Engineering (Jilin University), Ministry of Education, Changchun, Jilin Province, 130012, China. Electronic address: wangying2010@jlu.edu.cn. ^[5]

关键词 Distribution shifts Dynamic graphs representation learning Graph neural networks Hypernetwork

医学主题词人类(Humans);算法(Algorithms)

DOI 10.1016/j.neunet.2025.108006

PMID 40907361

发布时间 2025-12-17

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