Soil moisture forecasting in wireless sensor networks via spatiotemporal graph convolutional networks by Weixuan Wang, Yating Wei, Longfei Hao, Zushuai Wei, Tianjie Zhao

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Edge Convolution Graph Neural Network Assisted Power Allocation for Wireless IoT Networks by Jihyung Kim, Yeji Cho, Junghyun Kim

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Residual-enhanced graph convolutional networks with hypersphere mapping for anomaly detection in attributed networks by Wasim Khan, Afsaruddin Mohd, Mohammad Suaib, Mohammad Ishrat, Anwar Ahamed Shaikh, Syed Mohd Faisal

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PS-GCN: psycholinguistic graph and sentiment semantic fused graph convolutional networks for personality detection by Wenjuan Liu, Zhengyan Sun, Subo Wei, Shunxiang Zhang, Guangli Zhu, Lei Chen

“…To address this issue, this paper presents PS-GCN, a model integrating Psychological knowledge and Sentiment semantic features through Graph Convolution Networks. Firstly, the Bi-LSTM network captures local features of preprocessed sentences to accurately represent the output of sentence sentiment features. …”
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Relational Graph Construction Method and Information Management System Based on the Relational Graph Convolutional Network by Yun Dong, Xixiang Zhang, Zhongfeng Liang, Chao Liu, Liming Qin

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Rolling Bearing Fault Diagnosis via Temporal-Graph Convolutional Fusion by Fan Li, Yunfeng Li, Dongfeng Wang

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Hyperspectral Band Selection via Heterogeneous Graph Convolutional Self-Representation Network by Junde Chen, Wenzhao Li, Surendra Maharjan, Hesham El-Askary

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Graph Kolmogorov–Arnold Convolutional Network for Hyperspectral Image Classification by Hengyi Zheng, Hongjun Su, Zhaoyue Wu, Yiping Chen, Qian Du

“…However, two significant limitations (poor model scaling and lack of interpretability) impede GNNs ability to extract deeper features in the graph. Therefore, this article proposes a novel method called graph Kolmogorov–Arnold convolutional network (GKACN) where the Kolmogorov–Arnold network (KAN) theory-based convolutional operation is employed in the graph for HSIC. …”
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AFMF: adaptive fusion of multi-hop neighborhood features in graph convolutional network by Kang Liu, Xinyu Li, Lian Liu, Zhihao Xv, Aohang Pei, Runshi Ji

“…To address this issue, we propose a graph convolutional network based on Adaptive Fusion of Multi-hop Features, termed AFMF, which can adaptively generate feature fusion weights according to the features of multi-hop nodes, solving the over-smoothing problem caused by shared fusion weights. …”
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Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks by Jianhong Gan, Runqing Kang, Xun Deng, Chentao Mao, Zhibin Li, Peiyang Wei, Chunjiang Wu, Tongli He

“…This article proposes a dynamic spatiotemporal graph convolutional network (DSTGFP) model for multistation wind speed prediction to address this challenge. …”
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Few-shot traffic classification based on autoencoder and deep graph convolutional networks by Shengwei Xu, Jijie Han, Yilong Liu, Haoran Liu, Yijie Bai

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Rumor detection using dual embeddings and text-based graph convolutional network by Barsha Pattanaik, Sourav Mandal, Rudra M. Tripathy, Arif Ahmed Sekh

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The node importance evaluation method based on graph convolution in multilayer heterogeneous networks by Zhixing Chen, Jian Shu, Linlan Liu

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MulGCN: MultiGraph Convolutional Network for Aspect-Level Sentiment Analysis by Huyen Trang Phan, Van Du Nguyen, Ngoc Thanh Nguyen

Subjects: “…Graph convolutional network (GCN)…”
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Inverse link prediction with graph convolutional networks for knowledge-preserving sparsification in cheminformatics by Elnaz Bangian Tabrizi, Mehrdad Jalali, Mahboobeh Houshmand

“…This Inverse Link Prediction with Graph Convolutional Networks (ILP-GCN) framework offers a scalable and interpretable solution for cheminformatics, with broad applications in material discovery and beyond. …”
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Hand-aware graph convolution network for skeleton-based sign language recognition by Juan Song, Huixuechun Wang, Jianan Li, Jian Zheng, Zhifu Zhao, Qingshan Li

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STFGCN: Spatio-Temporal Fusion Graph Convolutional Networks for Subway Traffic Prediction by Xiaoxi Zhang, Zhanwei Tian, Yan Shi, Qingwen Guan, Yan Lu, Yujie Pan

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Semantics-Assisted Training Graph Convolution Network for Skeleton-Based Action Recognition by Huangshui Hu, Yu Cao, Yue Fang, Zhiqiang Meng

“…To address the lack of utilization of semantic information, this paper proposes a semantics-assisted training graph convolution network (SAT-GCN). By dividing the features outputted by the skeleton encoder into four parts and contrasting them with the text features generated by the text encoder, the obtained contrastive loss is used to guide the overall network training. …”
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A Dual-channel Progressive Graph Convolutional Network via subgraph sampling by Wenrui Guan, Xun Wang

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Classification of Neuropsychiatric Disorders via Brain-Region-Selected Graph Convolutional Network by Zhenzhe Qin, Yongbo Li, Xiaoying Song, Li Chai

“…For the classification of patients with neuropsychiatric disorders based on rs-fMRI data, this paper proposed a Brain-Region-Selected graph convolutional network (BRS-GCN). In order to effectively identify the most significant biomarkers associated with disease, we designed a novel ROI pooling score function. …”
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