Exploring the Latent Information in Spatial Transcriptomics Data via Multi‐View Graph Convolutional Network Based on Implicit Contrastive Learning by Sheng Ren, Xingyu Liao, Farong Liu, Jie Li, Xin Gao, Bin Yu

“…This study introduces STMIGCL, a novel framework that leverages a multi‐view graph convolutional network and implicit contrastive learning. …”
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GP-GCN: Global features of orthogonal projection and local dependency fused graph convolutional networks for aspect-level sentiment classification by Subo Wei, Guangli Zhu, Zhengyan Sun, Xiaoqing Li, TienHsiung Weng

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Crop Recommendation Systems Based on Soil and Environmental Factors Using Graph Convolution Neural Network: A Systematic Literature Review by P. Ayesha Barvin, T. Sampradeepraj

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FreqMGCN-Net: An IoT-Integrated Multi-Parallel Graph Convolutional Network with frequency attention for motor bearing fault diagnosis by Jicai Wang, Shahrum Abdullah, Chen Gao, Azli Arifin, Salvinder Singh Karam Sing

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Deep learning in-depth analysis of crystal graph convolutional neural networks: A new era in materials discovery and its applications by Qureshi Nilam, Bang Jinhong, Doh Jaehyeok

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A dual-stream ordered topology-aware network for accurate fish counting in aquaculture environments by Jiaming Xin, Zhengmeng Wu, Tongtong Gu, Yiying Wang, Dashe Li, Bin Wang

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PGCF: Perception graph collaborative filtering for recommendation by Caihong Mu, Keyang Zhang, Jiashen Luo, Yi Liu

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Multiscale Wavelet and Graph Network With Spectral Self-Attention for Hyperspectral Image Classification by Anyembe C. Shibwabo, Zou Bin, Tahir Arshad, Jorge Abraham Rios Suarez

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Pedestrian Trajectory Prediction Based on Dual Social Graph Attention Network by Xinhai Li, Yong Liang, Zhenhao Yang, Jie Li

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Enhancing Image Classification using Graph Attention Networks by Hasan Maher Ahmed

Subjects: “…image classification, graph attention networks, vision transformers, graph convolutional networks, artificial intelligence…”
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Hypergraph Convolution Network Classification for Hyperspectral and LiDAR Data by Lei Wang, Shiwen Deng

“…Although deep learning methods based on convolutional neural networks (CNNs), transformers, and graph convolutional networks (GCNs) have demonstrated promising results in fusing complementary multi-source data, existing methodologies demonstrate limited efficacy in capturing the intricate higher-order spatial–spectral dependencies among pixels. …”
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An Adaptive Graph Convolutional Network with Spatial Autocorrelation for Enhancing 3D Soil Pollutant Mapping Precision from Sparse Borehole Data by Huan Tao, Ziyang Li, Shengdong Nie, Hengkai Li, Dan Zhao

“…We propose an adaptive graph convolutional network with spatial autocorrelation (ASI-GCN) model to overcome this challenge. …”
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Leveraging molecular-QTL co-association to predict novel disease-associated genetic loci using a graph convolutional neural network by Julian Ng-Kee-Kwong, Andrew D. Bretherick

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Fault diagnosis of power transformers based on dissolved gas analysis and multi-kernel graph convolution network integrated with dual-channel classifiers by Xuebin Lv, Fuzheng Liu, Mingshun Jiang, Faye Zhang, Lei Jia

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APGCN-CF: A Spatio-Temporal-Aware Graph Convolutional Network Framework for Minor Agricultural Product Recommendation in Rural E-Commerce by Wenjin Hou, Ke Zhu, Pingzeng Liu, Honghua Jiang, Yan Zhang, Xinran Yu

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A transfer learning-based graph convolutional network for dynamic security assessment considering loss of synchronism of wind turbines and unknown faults by Sasan Azad, Mohammad Taghi Ameli, Amjad Anvari-Moghaddam, Miadreza Shafie-khah

“…To tackle these challenges, this paper introduces a new dynamic security index that considers the effects of loss of synchronism in power electronics-based units on DSA. Also, a graph convolutional network (GCN)-based model is developed to improve DSA accuracy by incorporating the topological information of the power system in the form of an adjacency matrix. …”
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A multi-graph convolutional network method for Alzheimer’s disease diagnosis based on multi-frequency EEG data with dual-mode connectivity by Qingjie Xu, Qingjie Xu, Libing An, Haiqiang Yang, Haiqiang Yang, Keum-Shik Hong, Keum-Shik Hong

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Author Correction: Hybridization of synergistic swarm and differential evolution with graph convolutional network for distributed denial of service detection and mitigation in IoT environment by Chukka Ramesh Babu, M. Suneetha, Mohammed Altaf Ahmed, Palamakula Ramesh babu, Mohamad Khairi Ishak, Hend Khalid Alkahtani, Samih M. Mostafa

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LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks by Bing Zhang, Haoyu Wang, Chao Ma, Hai Huang, Zhou Fang, Jiaxing Qu

“…The Graph Convolutional Autoencoder is employed for nonlinear feature extraction. …”
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A dynamic adaptive graph convolutional recurrent network model for efficient mid-short term prediction of global sea surface salinity by Guangwen Peng, Yingbing Liu, Cong Xiao, Wenying Du, Changjiang Xiao

“…To address these challenges, we propose a Dynamic Adaptive Graph Convolutional Recurrent Network (DAGCRN) for global SSS prediction. …”
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