.png){kind=icon}
返回
Graph isomorphism U-Net
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2023.121280.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Graph embedding learning is a fundamental task when dealing with diverse datasets. While encoder-decoder architectures, such as U-Nets, have shown great success in image pixel-wise prediction tasks, applying similar methods to graph data poses challenges due to the lack of natural pooling and up-sampling operations for graphs. Recent methods leverage learnable parameters to extract structural information from neural networks and extend pooling and unpooling to graphs using node features and graph structural information. This paper proposes a novel model called GIUNet (Graph Isomorphism U-Net) for the graph classification task. The proposed Graph U-Net structure is based on graph isomorphism convolution while using a comprehensive pqPooling layer. The pqPooling layer in our approach effectively combines node features and graph structure information during the graph down-sampling stage. To incorporate graph structure information, we utilize both the spectral representation and node centrality measurements. Node centrality measurements capture various structural aspects of nodes in the graph, while the spectral representation helps us focus on the informative low frequency components of the graph structure. Through ablation studies, we have demonstrated that leveraging the GIUNet model leads to significant improvements compared to state-of-the-art methods across multiple benchmark datasets.
Keyword:
Graph embedding
Graph U-nets
Graph isomorphism
Graph neural networks
Pooling layer
期刊
IF:
7.5
论文数:
3.0W
被引数:
10.2W
机构
引用论文
Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models图形神经网络可以为药物发现学习更好的分子表示吗？基于描述符和基于图的模型的比较研究
OAAI
OAAI分享收藏U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and ApplicationsU-net及其变体在医学图像分割中的理论与应用综述.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏Environmental Factors and Seasonality Affect the Concentration of Rotundone in Vitis vinifera L. cv. Shiraz WinePLOS ONEOAAI
PLOS ONEIF0
OAAI分享收藏
查看更多内容