Deep Learning Based Proactive Caching for Effective WSN-Enabled Vision Applications von Zhao, Huimin, Dai, Qingyun, Cai, Jun, Lei, Fangyuan

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SimGRL: a simple self-supervised graph representation learning framework via triplets von Huang, Da, Lei, Fangyuan, Zeng, Xi

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Higher-Order Graph Convolutional Networks With Multi-Scale Neighborhood Pooling for Semi-Supervised Node Classification von Liu, Xun, Xia, Guoqing, Lei, Fangyuan, Zhang, Yikuan, Chang, Shihui

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AdjMix: simplifying and attending graph convolutional networks von Liu, Xun, Lei, Fangyuan, Xia, Guoqing, Zhang, Yikuan, Wei, Wenguo

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Multi-order hypergraph convolutional networks integrated with self-supervised learning von Huang, Jiahao, Lei, Fangyuan, Jiang, Jianjian, Zeng, Xi, Ma, Ruijun, Dai, Qingyun

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Temporal group-aware graph diffusion networks for dynamic link prediction von Huang, Da, Lei, Fangyuan

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Sequential multi-view subspace clustering von Lei, Fangyuan, Li, Qin

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PID Controller-Guided Attention Neural Network Learning for Fast and Effective Real Photographs Denoising von Ma, Ruijun, Zhang, Bob, Zhou, Yicong, Li, Zhengming, Lei, Fangyuan

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Signal Feature Extract Based on Dual-Channel Wavelet Convolutional Network Mixed With Hypergraph Convolutional Network for Fault Diagnosis von Lei, Fangyuan, Luo, Xiangmin, Chen, Ziwei, Zhou, Houmian

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GPNet: Simplifying graph neural networks via multi-channel geometric polynomials von Liu, Xun, Ng, Alex Hay-Man, Lei, Fangyuan, Zhang, Yikuan, Li, Zhengming

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Multibranch Fusion: A Multibranch Attention Framework by Combining Graph Convolutional Network and CNN for Hyperspectral Image Classification von Liu, Xun, Ng, Alex Hay-Man, Ge, Linlin, Lei, Fangyuan, Liao, Xuejiao

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MulStepNET: stronger multi-step graph convolutional networks via multi-power adjacency matrix combination von Liu, Xun, Lei, Fangyuan, Xia, Guoqing

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Multihop Neighbor Information Fusion Graph Convolutional Network for Text Classification von Lei, Fangyuan, Liu, Xun, Li, Zhengming, Dai, Qingyun, Wang, Senhong

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Unveiling the potential of long-range dependence with mask-guided structure learning for hypergraph von Lei, Fangyuan, Huang, Jiahao, Jiang, Jianjian, Huang, Da, Li, Zhengming, Wang, Chang-Dong

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AHFormer: Hypergraph embedding coding transformer and adaptive aggregation network for intelligent fault diagnosis under noise interference von Lei, Fangyuan, Chen, Ziwei, Luo, Xiangmin, Xu, Long, Xue, Te, Jiang, Jianjian

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Multi-granularity hypergraph-guided transformer learning framework for visual classification von Jiang, Jianjian, Chen, Ziwei, Lei, Fangyuan, Xu, Long, Huang, Jiahao, Yuan, Xiaochen

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Multiple kernel-based anchor graph coupled low-rank tensor learning for incomplete multi-view clustering von Wang, Senhong, Cao, Jiangzhong, Lei, Fangyuan, Jiang, Jianjian, Dai, Qingyun, Ling, Bingo Wing-Kuen

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Graph convolutional networks with higher‐order pooling for semisupervised node classification von Lei, Fangyuan, Liu, Xun, Jiang, Jianjian, Liao, Liping, Cai, Jun, Zhao, Huimin

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Shallow convolutional neural network for image classification von Lei, Fangyuan, Liu, Xun, Dai, Qingyun, Ling, Bingo Wing-Kuen

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An Unsupervised Domain Adaption Method for Fault Diagnosis via Multichannel Variational Hypergraph Autoencoder von Luo, Xiangmin, Chen, Ziwei, Huang, Da, Lei, Fangyuan, Wang, Chang-Dong, Yi Liao, Iman

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