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Network Embedding

Network Embedding, also known as "Network Representation Learning", is a collective term for techniques for mapping graph nodes to vectors of real numbers in a multidimensional space. To be useful, a good embedding should preserve the structure of the graph. The vectors can then be used as input to various network and graph analysis tasks, such as link prediction

Source: Tutorial on NLP-Inspired Network Embedding

Papers

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Showing 176–200 of 403 papers

TitleStatusHype
Bib2vec: Embedding-based Search System for Bibliographic Information—0
A multi-domain VNE algorithm based on multi-objective optimization for IoD architecture in Industry 4.0—0
Dynamic Graph Embedding via LSTM History Tracking—0
Document Network Projection in Pretrained Word Embedding Space—0
BHIN2vec: Balancing the Type of Relation in Heterogeneous Information Network—0
A Multi-Domain VNE Algorithm based on Load Balancing in the IoT networks—0
Adversarial Network Embedding—0
A Block-based Generative Model for Attributed Networks Embedding—0
Document Network Embedding: Coping for Missing Content and Missing Links—0
DISCO: Influence Maximization Meets Network Embedding and Deep Learning—0
DINE: A Framework for Deep Incomplete Network Embedding—0
Beyond Node Embedding: A Direct Unsupervised Edge Representation Framework for Homogeneous Networks—0
A multi-domain virtual network embedding algorithm with delay prediction—0
Diffusion Maps for Textual Network Embedding—0
Diffusion Based Network Embedding—0
Barlow Graph Auto-Encoder for Unsupervised Network Embedding—0
Detecting Online Hate Speech: Approaches Using Weak Supervision and Network Embedding Models—0
Detecting local perturbations of networks in a latent hyperbolic embedding space—0
A Weakly Supervised Segmentation Network Embedding Cross-scale Attention Guidance and Noise-sensitive Constraint for Detecting Tertiary Lymphoid Structures of Pancreatic Tumors—0
A Model-data-driven Network Embedding Multidimensional Features for Tomographic SAR Imaging—0
Demographic Inference on Twitter using Recursive Neural Networks—0
DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks—0
Author Name Disambiguation via Heterogeneous Network Embedding from Structural and Semantic Perspectives—0
Selective Network Discovery via Deep Reinforcement Learning on Embedded Spaces—0
Network embedding unveils the hidden interactions in the mammalian virome—0
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