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https://openreview.net/forum?id=zIpx-MISaIA Graph Attention Network for Prostate Cancer Lymph Node Invasion Prediction | OpenReview A graph attention network (GAT) model combining radiomics and clinical data to improve the performance and interpretability of lymph node invasion prediction... graph attention network prostate cancer lymph node https://openreview.net/forum?id=K7cAyMYXJR&referrer=%5Bthe%20profile%20of%20Ziwei%20Shi%5D(%2Fprofile%3Fid%3D~Ziwei_Shi1) SGA-Net: A Sparse Graph Attention Network for Two-View Correspondence Learning | OpenReview Establishing reliable correspondences between two images is a fundamental and important task in computer vision. This paper proposes a novel network called... graph attention network https://aclanthology.org/2020.coling-main.69/ Syntax-Aware Graph Attention Network for Aspect-Level Sentiment Classification - ACL Anthology Lianzhe Huang, Xin Sun, Sujian Li, Linhao Zhang, Houfeng Wang. Proceedings of the 28th International Conference on Computational Linguistics. 2020. graph attention network https://www.mdpi.com/1424-8220/22/23/9272 Multi-Layer Graph Attention Network for Sleep Stage Classification Based on EEG Graph neural networks have been successfully applied to sleep stage classification, but there are still challenges: (1) How to effectively utilize epoch... graph attention network multi layer for sleep https://www.ojp.gov/library/publications/hyperbolic-graph-attention-network Hyperbolic Graph Attention Network | Office of Justice Programs By exploiting the graph attention network, the authors of this study learn robust node representations of graphs in hyperbolic spaces, utilizing the gyrovector... graph attention network hyperbolic office justice programs https://www.mdpi.com/1424-8220/21/24/8468 Cross-Attention Fusion Based Spatial-Temporal Multi-Graph Convolutional Network for Traffic Flow... Accurate traffic flow prediction is essential to building a smart transportation city. Existing research mainly uses a given single-graph structure as a model,... graph convolutional network