Research on Multi-Step Prediction of Pipeline Corrosion Rate Based on Adaptive MTGNN Spatio-Temporal Correlation Analysis by Mingyang Sun, Shiwei Qin

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DMR: disentangled and denoised learning for multi-behavior recommendation by Yijia Zhang, Wanyu Chen, Fei Cai, Zhenkun Shi, Feng Qi

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Multimodal data fusion for Alzheimer's disease based on dynamic heterogeneous graph convolutional neural network and generative adversarial network by Xiaoyu Chen, Shuaiqun Wang, Wei Kong

“…The proposed method designs private graph convolutional layers and shared heterogeneous attention layers, combining dynamic graph structure updates and graph structure regularization to dynamically enhance inter-modal relationships. …”
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MG6D: A Deep Fusion Approach for 6D Pose Estimation With Mamba and Graph Convolution Network by Jiaqi Zhu, Bin Li, Xinhua Zhao

“…A dynamic graph convolutional adaptive fusion module is then designed to enable cross-modal geometric consistency modeling via multi-modal feature integration. …”
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MolAttnNet: A Predictive Model for Organic Drug Solubility Based on Graph Convolutional Networks and Transformer-Attention by Chenxu Wang, Yijun Feng, Zhejie Xu, Xiaohui Xu, Bangguo Peng

“…The framework comprises three specialized modules: a Graph Convolutional Network for extracting local molecular structural features, a multi-granularity attention mechanism for capturing both local and global molecular dependencies, and an adaptive LSTM with chemically-informed forget gates for selective feature retention and noise attenuation. …”
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Data-Driven Dynamic Graph Convolution Transformer Network Model for EEG Emotion Recognition Under IoMT Environment by Xing Jin, Fa Zhu, Yu Shen, Gwanggil Jeon, David Camacho

“…Moreover, the graph convolution operations can effectively exploit the spatial information between different channels. …”
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MoAGL-SA: a multi-omics adaptive integration method with graph learning and self attention for cancer subtype classification by Lei Cheng, Qian Huang, Zhengqun Zhu, Yanan Li, Shuguang Ge, Longzhen Zhang, Ping Gong

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MONet: cancer driver gene identification algorithm based on integrated analysis of multi-omics data and network models by Yingzan Ren, Tiantian Zhang, Jian Liu, Fubin Ma, Jiaxin Chen, Ponian Li, Guodong Xiao, Chuanqi Sun, Yusen Zhang

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Heterogeneous network drug-target interaction prediction model based on graph wavelet transform and multi-level contrastive learning by Wenfeng Dai, Yanhong Wang, Shuai Yan, Qingzhi Yu, Xiang Cheng

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A Spatio-Temporal Joint Diagnosis Framework for Bearing Faults via Graph Convolution and Attention-Enhanced Bidirectional Gated Networks by Zhiguo Xiao, Xinyao Cao, Huihui Hao, Siwen Liang, Junli Liu, Dongni Li

“…To address these challenges, this paper proposes a joint diagnosis framework integrating graph convolutional networks (GCNs) with attention-enhanced bidirectional gated recurrent units (BiGRUs). …”
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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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Latent Graph Induction Networks and Dependency Graph Networks for Events Detection by Jing Yang, Hu Gao, Depeng Dang

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Pedestrian Trajectory Prediction via Window Attention and Spatial Graph Interaction Network by Xiang Gu, Chao Li, Jie Yang, Jing Wang, Qiwei Huang

“…In the spatial dimension, a hierarchical heterogeneous GCN (graph convolutional network) is constructed, combining pedestrian dynamic interaction graphs and scene semantic static graphs. …”
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Sketch Face Recognition Method Based on Local-Global Adapter by Huanyu Bian, Boqian Lv, Yanan Guo, Benkui Zhang, Kangning Du

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An automatic ICD coding method for clinical records based on deep neural network by Yichao DU, Tong XU, Jianhui MA, Enhong CHEN, Yi ZHENG, Tongzhu LIU, Guixian TONG

Subjects: “…ICD coding;multi-scale;residual network;graph convolutional network…”
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Latent Graph Attention for Spatial Context in Light-Weight Networks: Multi-Domain Applications in Visual Perception Tasks by Ayush Singh, Yash Bhambhu, Himanshu Buckchash, Deepak K. Gupta, Dilip K. Prasad

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Diagnosis Model for Refrigerant Charge Fault under Heating Conditions based on Multi-layer Convolution Neural Network by Cheng Hengda, Chen Huanxin, Li Zhengfei, Cheng Xiangdong

“…The performance of the refrigerant charge fault diagnosis model of variable refrigerant flow (VRF) system was evaluated with graphed experimental data. The results show that the model established by the "data graphing & multi-layer convolutional network" method can be effectively used for the refrigerant charge fault diagnosis of the VRF system. …”
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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

“…APGCN-CF implements a multi-module architecture encompassing graph structure construction, convolution-based feature learning, user similarity-based candidate generation, and preference probability-driven precise recommendation. …”
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MultiV_Nm: a prediction method for 2′-O-methylation sites based on multi-view features by Lei Bai, Fei Liu, Yile Wang, Junle Su, Lian Liu

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Knowledge graph-based entity alignment with unified representation for auditing by Youhua Zhou, Xueming Yan, Han Huang, Zhifeng Hao, Haofeng Zhu, Fangqing Liu

“…In this study, we propose a knowledge graph-based entity alignment approach with multi-attribute and weighted-relation fusion (KG-Marfia) for intelligent auditing. …”
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