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pro vyhledávání: '"Xia, Kaiwen"'
Graph Neural Networks (GNNs) excel at handling graph data but remain vulnerable to adversarial attacks. Existing defense methods typically rely on assumptions like graph sparsity and homophily to either preprocess the graph or guide structure learnin
Externí odkaz:
http://arxiv.org/abs/2410.12425
With the advent of the era of big data, massive information, expert experience, and high-accuracy models bring great opportunities to the information cascade prediction of public emergencies. However, the involvement of specialist knowledge from vari
Externí odkaz:
http://arxiv.org/abs/2404.01319
Publikováno v:
In Construction and Building Materials 25 October 2024 449
Publikováno v:
In Construction and Building Materials 20 September 2024 444
Publikováno v:
In Engineering Fracture Mechanics 20 September 2024 308
Publikováno v:
In Tectonophysics 22 August 2024 885
Publikováno v:
In Engineering Fracture Mechanics 5 August 2024 306
Autor:
Ma, Yueqiang, Xia, Kaiwen, Lei, Qinghua, Zhang, Chongyuan, Elsworth, Derek, Gan, Quan, Yuan, Liang
Publikováno v:
In International Journal of Rock Mechanics and Mining Sciences August 2024 180
Publikováno v:
In Energy Reviews December 2024 3(4)
Publikováno v:
In International Journal of Mining Science and Technology June 2024 34(6):799-819