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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 276–300 of 403 papers

TitleStatusHype
BHIN2vec: Balancing the Type of Relation in Heterogeneous Information Network—0
Bib2vec: Embedding-based Search System for Bibliographic Information—0
Big Networks: A Survey—0
Broad Learning for Healthcare—0
Can Network Embedding of Distributional Thesaurus be Combined with Word Vectors for Better Representation?—0
Hedging carbon risk with a network approach—0
Clustering Molecular Energy Landscapes by Adaptive Network Embedding—0
CoANE: Modeling Context Co-occurrence for Attributed Network Embedding—0
CoarSAS2hvec: Heterogeneous Information Network Embedding with Balanced Network Sampling—0
Collaborative filtering via heterogeneous neural networks—0
Community Aware Random Walk for Network Embedding—0
Community detection using low-dimensional network embedding algorithms—0
Complex Network Classification with Convolutional Neural Network—0
Compositional Network Embedding—0
Exact Recovery of Community Structures Using DeepWalk and Node2vec—0
Controlled Deep Reinforcement Learning for Optimized Slice Placement—0
COSINE: Compressive Network Embedding on Large-scale Information Networks—0
Cross Version Defect Prediction with Class Dependency Embeddings—0
Data-driven biological network alignment that uses topological, sequence, and functional information—0
Deep Adversarial Network Alignment—0
Deep Coevolutionary Network: Embedding User and Item Features for Recommendation—0
Deep Contrastive Multiview Network Embedding—0
Deep Feature Learning of Multi-Network Topology for Node Classification—0
Learning to Embed Categorical Features without Embedding Tables for Recommendation—0
DeepHE: Accurately Predicting Human Essential Genes based on Deep Learning—0
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