Search Results - "graph autoencoder"

RARE: Robust Masked Graph Autoencoder by Tu, Wenxuan, Liao, Qing, Zhou, Sihang, Peng, Xin, Ma, Chuan, Liu, Zhe, Liu, Xinwang, Cai, Zhiping, He, Kunlun

“…Masked graph autoencoder (MGAE) has emerged as a promising self-supervised graph pre-training (SGP…”
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Graph autoencoder-based unsupervised outlier detection by Du, Xusheng, Yu, Jiong, Chu, Zheng, Jin, Lina, Chen, Jiaying

“… To address this problem, we propose a novel graph neural network structure called the graph autoencoder (GAE…”
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Spectral-Spatial Feature Extraction With Dual Graph Autoencoder for Hyperspectral Image Clustering by Zhang, Yongshan, Wang, Yang, Chen, Xiaohong, Jiang, Xinwei, Zhou, Yicong

“… into feature extraction. To address these issues, in this paper, we propose a dual graph autoencoder (DGAE…”
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WAGE: Weight-Sharing Attribute-Missing Graph Autoencoder by Tu, Wenxuan, Zhou, Sihang, Liu, Xinwang, Cai, Zhiping, Zhao, Yawei, Liu, Yue, He, Kunlun

“…Attribute-missing graph learning, a common yet challenging problem, has recently attracted considerable attention. Existing efforts have at least one of the…”
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NodeHGAE: Node-oriented heterogeneous graph autoencoder by Zhu, Xiangkai, Li, Chao, Yan, Yeyu, Zhao, Zhongying, Duan, Hua, Zeng, Qingtian

“…Heterogeneous graph autoencoder (HGAE), as an unsupervised learning approach, aims to encode nodes and edges of heterogeneous graphs into low-dimensional vector representations, and simultaneously reconstruct the original graph structure…”
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Multi-view representation model based on graph autoencoder by Li, Jingci, Lu, Guangquan, Wu, Zhengtian, Ling, Fuqing

“… When some data labels are missing, graph autoencoder and graph variational autoencoder can perform outstanding abilities on node clustering or link prediction tasks…”
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Wasserstein Adversarially Regularized Graph Autoencoder by Liang, Huidong, Gao, Junbin

“…•Detailed experiment on link prediction, node clustering and embedding visualization. This paper introduces Wasserstein Adversarially Regularized Graph Autoencoder (WARGA…”
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Inferring gene regulatory network from single-cell transcriptomes with graph autoencoder model by Wang, Jiacheng, Chen, Yaojia, Zou, Quan

“… Then it utilizes a graph autoencoder model to embed the global regulatory information contained in the graph…”
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Hyperspectral Band Selection With Iterative Graph Autoencoder by Zhou, Yuan, Yao, Qingren, Huo, Shuwei, Li, Xiaofeng

“… To address this problem, we propose a data-driven method, named iterative graph autoencoder for BS (IGAEBS…”
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TGAE: Temporal Graph Autoencoder for Travel Forecasting by Wang, Qiang, Jiang, Hao, Qiu, Meikang, Liu, Yifeng, Ye, Dongsheng

“… To confront these challenges, we treat the dynamic traffic networks as multiple weighted directed network snapshots and propose a graph-based deep learning framework, Temporal Graph Autoencoder (TGAE…”
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Identification of microbe–disease signed associations via multi-scale variational graph autoencoder based on signed message propagation by 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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A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations by Shi, Zhuangwei, Zhang, Han, Jin, Chen, Quan, Xiongwen, Yin, Yanbin

“… Results We proposed an end-to-end model, VGAELDA, which integrates variational inference and graph autoencoders for lncRNA-disease associations prediction…”
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Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance by Zhu, Huan, Hao, Hongxia, Yu, Liang

“… Results In this work, we proposed a novel framework, Multi-scale Variational Graph AutoEncoder embedding Wasserstein distance (MVGAEW…”
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Community hiding using a graph autoencoder by Liu, Dong, Chang, Zhengchao, Yang, Guoliang, Chen, Enhong

“… To this end, we propose a new graph autoencoder for the community hiding algorithm, namely, GCH, which not only…”
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Aligning Dynamic Social Networks: An Optimization Over Dynamic Graph Autoencoder by Sun, Li, Zhang, Zhongbao, Wang, Feiyang, Ji, Pengxin, Wen, Jian, Su, Sen, Yu, Philip S.

“… Towards this end, we propose a novel Dynamic Graph autoencoder based dynamic social network Alignment approach, referred to as DGA , unfolding the fruitful dynamics of social networks for user alignment…”
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GAM-MDR: probing miRNA–drug resistance using a graph autoencoder based on random path masking by Zhou, Zhecheng, Du, Zhenya, Jiang, Xin, Zhuo, Linlin, Xu, Yixin, Fu, Xiangzheng, Liu, Mingzhe, Zou, Quan

“… To address this challenge, we introduce the GAM-MDR model, which combines the graph autoencoder (GAE…”
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Convolutional Graph Autoencoder: A Generative Deep Neural Network for Probabilistic Spatio-Temporal Solar Irradiance Forecasting by Khodayar, Mahdi, Mohammadi, Saeed, Khodayar, Mohammad E., Wang, Jianhui, Liu, Guangyi

“… This probabilistic data generation model, i.e., convolutional graph autoencoder (CGAE), is devised based on the localized first-order approximation…”
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Multi-sample dual-decoder graph autoencoder by He, Mengyao, Zhao, Qingqing, Zhang, Han

“… Generative self-supervised learning, especially graph autoencoders (GAEs), can prevent the above dependence and has been demonstrated as an effective approach…”
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Dual-decoder graph autoencoder for unsupervised graph representation learning by Sun, Dengdi, Li, Dashuang, Ding, Zhuanlian, Zhang, Xingyi, Tang, Jin

“… Recently, graph autoencoders have been proven to be an effective way to solve this problem in some attributed networks…”
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Weighted dynamic network link prediction based on graph autoencoder by Mei, Peng, Zhao, Yuhong, Wang, Jingyu, Liang, Yefei

“…With the development of deep learning, Graph Autoencoders (GAE) within unsupervised learning frameworks have been widely applied to representation learning in dynamic networks…”
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