Výsledky vyhledávání - "Graph autoencoder"

VIGA: A variational graph autoencoder model to infer user interest representations for recommendation Autor Gan, Mingxin, Zhang, Hang

“… To overcome these limitations, we propose a variational inference-based graph autoencoder (VIGA) model to explore a multivariate distribution over latent representations for recommendation…”
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Spatiotemporal Graph Autoencoder Network for Skeleton-Based Human Action Recognition Autor Abduljalil, Hosam, Elhayek, Ahmed, Marish Ali, Abdullah, Alsolami, Fawaz

“… In this study, we propose a novel, highly accurate spatiotemporal graph autoencoder network for HAR, designated as GA-GCN…”
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Graph-based learning for sleep microarchitecture: a hybrid graph autoencoder and graph attention network approach Autor Kurisinkal Augustine, Amala Ann, Vaidhehi

“…: We developed a graph autoencoder (GAE) combined with a Graph attention network (GAT) to analyze polysomnography (PSG…”
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Robust Graph Autoencoder-Based Detection of False Data Injection Attacks Against Data Poisoning in Smart Grids Autor Takiddin, Abdulrahman, Ismail, Muhammad, Atat, Rachad, Davis, Katherine R., Serpedin, Erchin

“…) of existing detectors significantly deteriorate by up to <inline-formula><tex-math notation="LaTeX">\text{9}\text{--}\text{29}{\%}</tex-math></inline-formula> when subject to data poisoning…”
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An Edge Feature Inclusive Variational Graph Autoencoder for Pet-Driven Alzheimer's Diagnosis Autor Gurbuz, Saruhan Mete, Adel, Mouloud

“… We propose GINEVGAE(Modified Graph Isomorphism Network with Variational Graph Autoencoder, a novel variational graph autoencoder that leverages GINEConv…”
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MSLTE: multiple self-supervised learning tasks for enhancing EEG emotion recognition Autor Li, Guangqiang, Chen, Ning, Niu, Yixiang, Xu, Zhangyong, Dong, Yuxuan, Jin, Jing, Zhu, Hongqin

“… learning-based feature reconstruction tasks combining masked graph autoencoders (GAE) are constructed…”
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A Variational Graph Autoencoder for Manipulation Action Recognition and Prediction Autor Akyol, Gamze, Sariel, Sanem, Aksoy, Eren Erdal

“… Different from the related works, we here introduce a deep graph autoencoder to jointly learn recognition and prediction…”
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A Variational Graph Autoencoder for Manipulation Action Recognition and Prediction Autor Akyol, Gamze, Sariel, Sanem, Eren Erdal Aksoy

“… Different from the related works, we here introduce a deep graph autoencoder to jointly learn recognition and prediction…”
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Cross-Group Brain Network Topology Propagation Model with Graph Attention Mechanism Autor Yu, Jing, Li, Shengrong, Ma, Kai, Wan, Peng, Sun, Liang, Zhu, Qi

“… Firstly, we extract the functional brain network topology of healthy subjects and patients and adaptively evaluate the centrality distribution of brain regions by the PageRank algorithm…”
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CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics Autor Bafna, Mihir, Li, Hechen, Zhang, Xiuwei

“… However, in reality, the two processes do not exist in isolation and are subject to spatial constraints…”
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A Graph-Based Generative Adversarial Network Model for Inferring Task-State from Resting-State Functional Connectivity Networks Autor Jin, Tao, Guan, Hongzheng, Xiao, Li, Qu, Gang, Wang, Yu-Ping

“… In this paper, we propose a Multiple Graph Autoencoder based Generative Adversarial Network (MGAE-GAN) model to enable the inference of ts-FCNs from rs-FCNs…”
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Probing the Substructure of Jets With Machine Learning Autor Athanasakos, Dimitrios

“… We introduce Jet Flow Networks (JFNs), a novel deep learning framework that uses reclustered subjects as input…”
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Graph Based Business Process Anomaly Detection with Edge Feature Reconstruction and Advanced Linear Networks Autor Ayaz, Teoman Berkay, Cevik, Rabia, Ozcan, Alper, Akbulut, Akhan

“…Business Process Management (BPM) as an inter-disciplinary field between Managerial Sciences and Computer Science is a subject ever-increasing in importance…”
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On the Power of Edge Independent Graph Models Autor Chanpuriya, Sudhanshu, Musco, Cameron, Sotiropoulos, Konstantinos, Tsourakakis, Charalampos E

“… Such models include both the classic Erd\"{o}s-R\'{e}nyi and stochastic block models, as well as modern generative models such as NetGAN, variational graph autoencoders, and CELL…”
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Predicting potential drug targets and repurposable drugs for COVID-19 via a deep generative model for graphs Autor Ray, Sumanta, Lall, Snehalika, Mukhopadhyay, Anirban, Bandyopadhyay, Sanghamitra, Schönhuth, Alexander

“…Coronavirus Disease 2019 (COVID-19) has been creating a worldwide pandemic situation. Repurposing drugs, already shown to be free of harmful side effects, for…”
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