/awesome-network-embedding

A curated list of network embedding techniques.

awesome-network-embedding

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Also called network representation learning, graph embedding, knowledge embedding, etc.

The task is to learn the representations of the vertices from a given network.

Paper References with the implementation(s)

Paper References

Deep Feature Learning for Graphs, arxiv'17

Watch Your Step: Learning Graph Embeddings Through Attention, arxiv'17

Fast Linear Model for Knowledge Graph Embeddings, arxiv'17

Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec, arxiv'17

A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications, arxiv'17

Representation Learning on Graphs: Methods and Applications, IEEE DEB'17

CONE, CONE: Community Oriented Network Embedding, arxiv'17

LANE, Label Informed Attributed Network Embedding, WSDM'17

Graph2Gauss, Deep Gaussian Embedding of Attributed Graphs: Unsupervised Inductive Learning via Ranking, arxiv [Bonus Animation]

Scalable Graph Embedding for Asymmetric Proximity, AAAI'17

Structural Deep Network Embedding, KDD'16

Query-based Music Recommendations via Preference Embedding, RecSys'16

Tri-party deep network representation, IJCAI'16

Heterogeneous Network Embedding via Deep Architectures, KDD'15

Neural Word Embedding As Implicit Matrix Factorization, NIPS'14

Distributed large-scale natural graph factorization, WWW'13

From Node Embedding To Community Embedding, arxiv

Walklets: Multiscale Graph Embeddings for Interpretable Network Classification, arxiv

Comprehend DeepWalk as Matrix Factorization, arxiv

Conference & Workshop

13th International Workshop on Mining and Learning with Graphs, MLG'17

Related List

awesome-embedding-models

Must-read papers on network representation learning (NRL) / network embedding (NE)

Must-read papers on knowledge representation learning (KRL) / knowledge embedding (KE)

Network Embedding Resources

awesome-embedding-models

2vec-type embedding models

Related Project

Stanford Network Analysis Project website