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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 351–400 of 403 papers

TitleStatusHype
Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search—0
HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding—0
Hierarchical Graph Neural Networks—0
High-order joint embedding for multi-level link prediction—0
High Tension Lines: Predicting robustness of high-voltage power-grids to cascading failure using network embedding—0
Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank—0
HONEM: Learning Embedding for Higher Order Networks—0
Hyperbolic Multiplex Network Embedding with Maps of Random Walk—0
Hyperbolic Node Embedding for Signed Networks—0
Identifying Transition States of Chemical Kinetic Systems using Network Embedding Techniques—0
Identity-sensitive Word Embedding through Heterogeneous Networks—0
Improved Deep Embeddings for Inferencing with Multi-Layered Networks—0
Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment—0
Improving Skip-Gram based Graph Embeddings via Centrality-Weighted Sampling—0
Improving Textual Network Embedding with Global Attention via Optimal Transport—0
Network embedding unveils the hidden interactions in the mammalian virome—0
Independent Asymmetric Embedding for Information Diffusion Prediction on Social Networks—0
Inductive Graph Embeddings through Locality Encodings—0
Integrated Node Encoder for Labelled Textual Networks—0
Interaction-Aware Topic Model for Microblog Conversations through Network Embedding and User Attention—0
IoV Scenario: Implementation of a Bandwidth Aware Algorithm in Wireless Network Communication Mode—0
An Isolation-Aware Online Virtual Network Embedding via Deep Reinforcement Learning—0
JITuNE: Just-In-Time Hyperparameter Tuning for Network Embedding Algorithms—0
Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks—0
Just Propagate: Unifying Matrix Factorization, Network Embedding, and LightGCN for Link Prediction—0
Large-scale Gender/Age Prediction of Tumblr Users—0
Large-Scale Network Embedding in Apache Spark—0
Large-Scale Privacy-Preserving Network Embedding against Private Link Inference Attacks—0
Latent Network Embedding via Adversarial Auto-encoders—0
Layer-stacked Attention for Heterogeneous Network Embedding—0
Learning a Deep Part-based Representation by Preserving Data Distribution—0
Learning Asymmetric Embedding for Attributed Networks via Convolutional Neural Network—0
Learning Depth from Single Images with Deep Neural Network Embedding Focal Length—0
Learning Document Embeddings With CNNs—0
Learning Embeddings of Directed Networks with Text-Associated Nodes---with Applications in Software Package Dependency Networks—0
Learning Large-scale Network Embedding from Representative Subgraph—0
MANELA: A Multi-Agent Algorithm for Learning Network Embeddings—0
MEGAN: A Generative Adversarial Network for Multi-View Network Embedding—0
MetaMIML: Meta Multi-Instance Multi-Label Learning—0
Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction—0
MS-IMAP -- A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning—0
Multi-Aspect Temporal Network Embedding: A Mixture of Hawkes Process View—0
Multi-Hot Compact Network Embedding—0
Multimodal Deep Network Embedding with Integrated Structure and Attribute Information—0
Multi Objective Resource Optimization of Wireless Network Based on Cross Domain Virtual Network Embedding—0
Multi-Vector Embedding on Networks with Taxonomies—0
Multi-View Dynamic Heterogeneous Information Network Embedding—0
Multi-View Network Embedding Via Graph Factorization Clustering and Co-Regularized Multi-View Agreement—0
MUSE: Multi-faceted Attention for Signed Network Embedding—0
NECA: Network-Embedded Deep Representation Learning for Categorical Data—0
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