Výsledky vyhľadávania - "Graph autoencoder (GAE)"

Graph autoencoder (GAE) for community detection in social networks Autor Joshi, Pratibha, Singh, Buddha

“… This paper proposes a graph autoencoder (GAE)-based method for community detection in social networks…”
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Correction to: Graph autoencoder (GAE) for community detection in social networks Autor Joshi, Pratibha, Singh, Buddha

“…The higher value of Euclidean distance shows the nodes are having lower proximity. 6 ei,j=∑k=1ngi,j,k2wheredi,j,k=ai,k-aj,k 7…”
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A Comprehensive Survey on Graph Neural Networks Autor Wu, Zonghan, Pan, Shirui, Chen, Fengwen, Long, Guodong, Zhang, Chengqi, Yu, Philip S.

“…Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and…”
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A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection Autor Zhang, Dai-Jun, Gao, Ying-Lian, Zhao, Jing-Xiu, Zheng, Chun-Hou, Liu, Jin-Xing

“… To utilize single-cell data more efficiently and to better explore the heterogeneity among cells, a new graph autoencoder (GAE…”
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GAM-MDR: probing miRNA–drug resistance using a graph autoencoder based on random path masking Autor 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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Adversarial Regularized Graph Autoencoder for Intelligent Anomaly Detection With Multisensor Signal Fusion Autor Li, Yingchun, Sun, Yu, Chen, Xuefeng, He, Qingbo, Long, Xinhua, Peng, Zhike, Yang, Laihao

“… Integrating adversarial training into the graph autoencoder (GAE) framework imposes regularization on the latent…”
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Hyperspectral Band Selection With Iterative Graph Autoencoder Autor Zhou, Yuan, Yao, Qingren, Huo, Shuwei, Li, Xiaofeng

“…Hyperspectral band selection (BS) is an important task for hyperspectral image (HSI) processing, which aims to select a discriminative and low-redundant band…”
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Graph Autoencoder-Based Power Attacks Detection for Resilient Electrified Transportation Systems Autor Fahim, Shahriar Rahman, Atat, Rachad, Kececi, Cihat, Takiddin, Abdulrahman, Ismail, Muhammad, Davis, Katherine R., Serpedin, Erchin

“…The interdependence of power and electrified transportation systems introduces new challenges to the reliability and resilience of charging infrastructure…”
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Learning-Based Proactive and Adaptive Link Flooding Attack Mitigation in AIoT Autor Xia, Yu, Zhang, Weiting, Liu, Ying, Kang, Jiawen, Zhang, Hongke

“…Artificial Intelligence of Things (AIoT) is a new networking paradigm incorporating AI and IoT, empowering multiple industries. Due to the high value of AI…”
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The effectiveness of intervention measures on MERS-CoV transmission by using the contact networks reconstructed from link prediction data Autor Kim, Eunmi, Kim, Yunhwan, Jin, Hyeonseong, Lee, Yeonju, Lee, Hyosun, Lee, Sunmi

“…Mitigating the spread of infectious diseases is of paramount concern for societal safety, necessitating the development of effective intervention measures…”
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VGAEDTI: drug-target interaction prediction based on variational inference and graph autoencoder Autor Zhang, Yuanyuan, Feng, Yinfei, Wu, Mengjie, Deng, Zengqian, Wang, Shudong

“…Motivation Accurate identification of Drug-Target Interactions (DTIs) plays a crucial role in many stages of drug development and drug repurposing. (i)…”
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Robustness meets accuracy in adversarial training for graph autoencoder Autor Zhou, Xianchen, Hu, Kun, Wang, Hongxia

“…Graph autoencoder (GAE) is an effective deep method for graph embedding, while it is vulnerable to the graph adversarial attacks…”
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Attention-based deep clustering method for scRNA-seq cell type identification Autor Li, Shenghao, Guo, Hui, Zhang, Simai, Li, Yizhou, Li, Menglong

“…Single-cell sequencing (scRNA-seq) technology provides higher resolution of cellular differences than bulk RNA sequencing and reveals the heterogeneity in…”
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Multitask joint learning with graph autoencoders for predicting potential MiRNA-drug associations Autor Zhong, Yichen, Shen, Cong, Xi, Xiaoting, Luo, Yuxun, Ding, Pingjian, Luo, Lingyun

“…The occurrence of many diseases is associated with miRNA abnormalities. Predicting potential drug-miRNA associations is of great importance for both disease…”
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Spatiotemporal associations between air pollution and emergency room visits for cardiovascular and cerebrovascular diseases in Korea using a multivariate graph autoencoder modeling approach: an ecological study Autor Wang, Sohee, Jeong, Seungpil, Ha, Eunhee

“…Purpose: This study aimed to assess the spatiotemporal associations between air pollution and emergency room visits for cardiovascular and cerebrovascular diseases in South Korea using a graph autoencoder (GAE…”
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scLEGA: an attention-based deep clustering method with a tendency for low expression of genes on single-cell RNA-seq data Autor Liu, Zhenze, Liang, Yingjian, Wang, Guohua, Zhang, Tianjiao

“…Abstract Single-cell RNA sequencing (scRNA-seq) enables the exploration of biological heterogeneity among different cell types within tissues at a resolution…”
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SGAE-MDA: Exploring the MiRNA-disease associations in herbal medicines based on semi-supervised graph autoencoder Autor Xu, Lei, Fu, Xiangzheng, Zhuo, Linlin, Zhou, Zhecheng, Liao, Xuefeng, Tian, Sha, Kang, Ruofei, Chen, Yifan

“…Research indicates that miRNAs present in herbal medicines are crucial for identifying disease markers, advancing gene therapy, facilitating drug delivery, and…”
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Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification Autor Noman, Fuad, Ting, Chee-Ming, Kang, Hakmook, Phan, Raphael C.-W., Ombao, Hernando

“…). We introduce a novel graph autoencoder (GAE) architecture, built upon graph convolutional networks (GCNs…”
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ConSpaS: a contrastive learning framework for identifying spatial domains by integrating local and global similarities Autor Wu, Siyao, Qiu, Yushan, Cheng, Xiaoqing

“…Abstract Spatial transcriptomics is a rapidly growing field that aims to comprehensively characterize tissue organization and architecture at single-cell or…”
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Node embedding-based graph autoencoder outlier detection for adverse pregnancy outcomes Autor Khan, Wasif, Zaki, Nazar, Ahmad, Amir, Masud, Mohammad M., Govender, Romana, Rojas-Perilla, Natalia, Ali, Luqman, Ghenimi, Nadirah, Ahmed, Luai A.

“… The graph autoencoder (GAE) was trained by applying…”
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