Results 1 to 10 of about 170,883 (277)
Variational quantum algorithm for node embedding [PDF]
Fundamental ResearchQuantum machine learning has made remarkable progress in many important tasks. However, the gate complexity of the initial state preparation is seldom considered in lots of quantum machine learning algorithms, making them non-end-to-end.
Zeng-rong Zhou, Hang Li, Gui-Lu Long
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Node embedding-based graph autoencoder outlier detection for adverse pregnancy outcomes [PDF]
Scientific Reports, 2023 Adverse pregnancy outcomes, such as low birth weight (LBW) and preterm birth (PTB), can have serious consequences for both the mother and infant. Early prediction of such outcomes is important for their prevention.
Wasif Khan +8 more
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Dynamic Community Detection Method of a Social Network Based on Node Embedding Representation
Mathematics, 2022 The node embedding method enables network structure feature learning and representation for social network community detection. However, the traditional node embedding method only focuses on a node’s individual feature representation and ignores the ...
Bo Zhang +6 more
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Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network Embedding [PDF]
Data Science and Engineering, 2019 Network embedding methodologies, which learn a distributed vector representation for each vertex in a network, have attracted considerable interest in recent years.
Vachik S. Dave +3 more
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Node and Edge Joint Embedding for Heterogeneous Information Network
Big Data Mining and AnalyticsDue to the heterogeneity of nodes and edges, heterogeneous network embedding is a very challenging task to embed highly coupled networks into a set of low-dimensional vectors.
Lei Chen +3 more
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IEEE Access, 2018 Network virtualization (NV) is one crucial attribute for the next-generation network. Virtual network embedding (VNE) is known to be the resource allocation problem in NV content.
Haotong Cao +5 more
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Method of Attributed Heterogeneous Network Embedding with Multiple Features [PDF]
Jisuanji kexue, 2022 Network embedding aims to represent nodes in unstructured network with low-dimensional,real-valued vectors,so that node embedding can retain the structural and attribute features of the original network as much as possible.However,current research mainly
TANG Qi-you, ZHANG Feng-li, WANG Rui-jin, WANG Xue-ting, ZHOU Zhi-yuan, HAN Ying-jun
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Attribute Network Representation Learning Based on Global Attention [PDF]
Jisuanji kexue, 2021 The attribute network not only has complex topology,its nodes also contain rich attribute information.Attribute network represent learning methods simultaneously extracts network topology and node attribute information to learn low-dimensional vector ...
XU Ying-kun, MA Fang-nan, YANG Xu-hua, YE Lei
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Node Embedding Method Based on Folded Path Aggregation on Attributed Network [PDF]
Jisuanji gongcheng, 2023 Attributed network embedding is a challenging task in the field of graph analysis.It aims to learn the low-dimensional vector representation of nodes from the network topology and node attributes of the network while maintaining its structure and ...
Mingchang BAI
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A Link Stress-related Virtual Network Embedding Algorithm [PDF]
Jisuanji gongcheng, 2016 Aiming at the problem of high link stress in substrate network caused by traditional Virtual Network Embedding(VNE) algorithm,a new VNE algorithm is proposed.In the stage of node embedding,the importance degree of node in network is gotten by its ...
ZHANG Jingjing,ZHAO Chenggui,YUAN Jianming
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