中世纪
发表于 2025-3-30 10:05:13
An Empirical Study of the Expressiveness of Graph Kernels and Graph Neural Networksble interest in determining the expressive power mainly of graph neural networks and of graph kernels, to a lesser extent. Most studies have focused on the ability of these approaches to distinguish non-isomorphic graphs or to identify specific graph properties. However, there is often a need for al
institute
发表于 2025-3-30 14:24:51
Multi-resolution Graph Neural Networks for PDE Approximatione solution of complex physical problems, in particular relying on Graph Neural Networks applied on a mesh of the domain at hand. On the other hand, state-of-the-art deep approaches of image processing use different resolutions to better handle the different scales of the images, thanks to pooling an
兵团
发表于 2025-3-30 19:20:41
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Diluge
发表于 2025-3-31 00:39:41
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容易做
发表于 2025-3-31 01:10:46
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辞职
发表于 2025-3-31 07:27:37
https://doi.org/10.1007/978-3-662-53310-9d on the famed U-Net. These approaches are experimentally validated on a diffusion problem, compared with projected CNN approach and the experiments witness their efficiency, as well as their generalization capabilities.
落叶剂
发表于 2025-3-31 12:23:49
https://doi.org/10.1007/978-3-662-53310-9the tail entities. Based on that, each relation is a rotation from the head entities to the tail entities on the hyperplane in complex vector space. Experiments on well-known datasets show the improvement of the proposed model compared to other models.
CHURL
发表于 2025-3-31 14:53:32
Grundlagen zum Schneideneingriff,ple Feed-forward based Interaction Model (FIM) and a Convolutional network based Interaction Model (CIM). Through extensive experiments conducted on three benchmark datasets, we demonstrate the advantages of our interaction mechanism, both of them achieving state-of-the-art performance consistently.
官僚统治
发表于 2025-3-31 21:26:26
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评论性
发表于 2025-4-1 01:04:28
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