Suchergebnisse - "variational graph autoencoder"

Cross-domain recommendation via knowledge distillation von Li, Xiuze, Huang, Zhenhua, Wu, Zhengyang, Wang, Changdong, Chen, Yunwen

“… Recommendation systems frequently suffer from data sparsity, resulting in less-than-ideal recommendations. A prominent solution to this problem is Cross-Domain …”
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Enhancing effective connection with link prediction for session-based recommendation von Wang, Hui, You, Junjie, Yi, Jianbing, Liu, Junyan, Huang, Runjie

“… The core objective of session-based recommendation (SBR) is to precisely capture user interest preferences from massive candidate items by modeling short-term …”
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Clustering Diffusion Model with Frequency-Signal Modulation for Variational Graph Autoencoders von Cheng, Junwei, Liang, Ke, Feng, Pengxing, Liu, Weixiong, Tang, Yong, He, Chaobo

“… Variational autoencoders (VAEs) have been widely used for node clustering, with existing methods mainly focusing on enhancing the expressiveness of their …”
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Variational graph autoencoder-driven balancing strategy for multimodal multi-objective optimization von Yang, Lei, Zhang, Erlei, Dang, Qianlong

“… Multimodal multi-objective optimization aims to balance the diversity and the convergence to obtain multiple complete and uniform Pareto optimal solution sets …”
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Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance von Zhu, Huan, Hao, Hongxia, Yu, Liang

“… Background Enormous clinical and biomedical researches have demonstrated that microbes are crucial to human health. Identifying associations between microbes …”
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LDA-VGHB: identifying potential lncRNA–disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine von Peng, Lihong, Huang, Liangliang, Su, Qiongli, Tian, Geng, Chen, Min, Han, Guosheng

“… Long noncoding RNAs (lncRNAs) participate in various biological processes and have close linkages with diseases. In vivo and in vitro experiments have …”
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Grade: Generative graph contrastive learning for multimodal recommendation von Ping, Yu-Chao, Wang, Shu-Qin, Yang, Zi-Yi, Dong, Yong-Quan, Hu, Meng-Xiang, Zhang, Pei-Lin

“… Multimodal recommender systems based on graph convolutional networks have made significant progress by integrating multiple modal data for item recommendation …”
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Disentangled-feature and composite-prior VAE on social recommendation for new users von Li, Nuo, Guo, Bin, Liu, Yan, Yu, Zhiwen

“… Social recommendation has been an effective approach to solve the new user recommendation problem based on user-item interactions and user-user social …”
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Dual stream fusion link prediction for sparse graph based on variational graph autoencoder and pairwise learning von Li, Xun, Cai, Hongyun, Feng, Chuan, Zhao, Ao

“… Recently, link prediction methods based graph neural networks have garnered significant attention and achieved great success on large datasets. However, …”
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Collaborative Decision-Reinforced Self-Supervision for Attributed Graph Clustering von Zhu, Pengfei, Li, Jialu, Wang, Yu, Xiao, Bin, Zhao, Shuai, Hu, Qinghua

“… Attributed graph clustering aims to partition nodes of a graph structure into different groups. Recent works usually use variational graph autoencoder (VGAE) …”
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De novo reconstruction of cell interaction landscapes from single-cell spatial transcriptome data with DeepLinc von Li, Runze, Yang, Xuerui

“… Based on a deep generative model of variational graph autoencoder (VGAE), we develop a new method, DeepLinc (deep learning framework for Landscapes of …”
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Unveiling community structures in static networks through graph variational Bayes with evolution information von Cheng, Junwei, He, Chaobo, Han, Kunlin, Chen, Gangbin, Liang, Wanying, Tang, Yong

“… With the rapid development of graph variational Bayes theory, some representative community detection methods have been proposed. Although these methods are …”
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Predicting miRNA-Disease Associations Based On Multi-View Variational Graph Auto-Encoder With Matrix Factorization von Ding, Yulian, Lei, Xiujuan, Liao, Bo, Wu, Fang-Xiang

“… MicroRNAs (miRNAs) have been proved to play critical roles in diverse biological processes, including the human disease development process. Exploring the …”
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Identification of microbe–disease signed associations via multi-scale variational graph autoencoder based on signed message propagation von Zhu, Huan, Hao, Hongxia, Yu, Liang

“… Background Plenty of clinical and biomedical research has unequivocally highlighted the tremendous significance of the human microbiome in relation to human …”
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Deep graph embedding learning based on multi-variational graph autoencoders for POI recommendation von Gong, Weihua, Shen, Genhang, Zhao, Anlun, Yang, Lianghuai, Cheng, Zhen

“… Recently, point-of-interest (POI) recommendation has become a popular research hotspot in heterogeneous location-based social network (LBSN). One major …”
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Accurate identification of snoRNA targets using variational graph autoencoder to advance the redevelopment of traditional medicines von Wang, Zhina, Chen, Yangyuan, Ma, Hongming, Gao, Hong, Zhu, Yangbin, Wang, Hongwu, Zhang, Nan

“… Existing studies indicate that dysregulation or abnormal expression of small nucleolar RNA (snoRNA) is closely associated with various diseases, including lung …”
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Attention-guided variational graph autoencoders reveal heterogeneity in spatial transcriptomics von Lei, Lixin, Han, Kaitai, Wang, Zijun, Shi, Chaojing, Wang, Zhenghui, Dai, Ruoyan, Zhang, Zhiwei, Wang, Mengqiu, Guo, Qianjin

“… The latest breakthroughs in spatially resolved transcriptomics technology offer comprehensive opportunities to delve into gene expression patterns within the …”
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Predicting Protein-Protein Interactions Using Sequence and Network Information via Variational Graph Autoencoder von Luo, Xin, Wang, Liwei, Hu, Pengwei, Hu, Lun

“… Protein-protein interactions (PPIs) play a critical role in the proteomics study, and a variety of computational algorithms have been developed to predict …”
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GraphCVAE: Uncovering cell heterogeneity and therapeutic target discovery through residual and contrastive learning von Zhang, Zhiwei, Wang, Mengqiu, Dai, Ruoyan, Wang, Zhenghui, Lei, Lixin, Zhao, Xudong, Han, Kaitai, Shi, Chaojing, Guo, Qianjin

“… Advancements in Spatial Transcriptomics (ST) technologies in recent years have transformed the analysis of tissue structure and function within spatial …”
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A Variational Graph Autoencoder Aided Canonical Correlation Analysis-Based Online Abnormal Patterns Detection Method for Buildings HVAC Systems von Pan, Xiaogang, Deng, Qiao, Jiao, Yuanyuan, Chen, Zhiwen

“… Heating, Ventilation, and Air Conditioning (HVAC) systems have become essential components of contemporary life, extensively employed in commercial and …”
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