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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

Showing 251275 of 403 papers

TitleStatusHype
Network2Vec Learning Node Representation Based on Space Mapping in Networks0
HiGitClass: Keyword-Driven Hierarchical Classification of GitHub RepositoriesCode1
Tutorial on NLP-Inspired Network Embedding0
RiWalk: Fast Structural Node Embedding via Role IdentificationCode0
Dynamic Embedding on Textual Networks via a Gaussian ProcessCode0
Improving Textual Network Learning with Variational Homophilic EmbeddingsCode0
Neural Embedding Propagation on Heterogeneous NetworksCode0
Multi-scale Attributed Node EmbeddingCode0
Selective Network Discovery via Deep Reinforcement Learning on Embedded Spaces0
Temporal Network Embedding with Micro- and Macro-dynamicsCode0
HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding0
Fast and Accurate Network Embeddings via Very Sparse Random ProjectionCode1
Adversarial Training Methods for Network EmbeddingCode1
Initialization for Network Embedding: A Graph Partition Approach0
NETR-Tree: An Eifficient Framework for Social-Based Time-Aware Spatial Keyword Query0
LEAP nets for power grid perturbationsCode0
On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications0
AHINE: Adaptive Heterogeneous Information Network Embedding0
MEGAN: A Generative Adversarial Network for Multi-View Network Embedding0
HONEM: Learning Embedding for Higher Order Networks0
Domain-adversarial Network AlignmentCode0
Deep Hashing for Signed Social Network Embedding0
ProNE: Fast and Scalable Network Representation LearningCode0
DynWalks: Global Topology and Recent Changes Awareness Dynamic Network EmbeddingCode1
IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for RecommendationCode0
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