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awesome-network-embedding
Also called network representation learning, graph embedding, knowledge embedding, etc.
The task is to learn the representations of the vertices from a given network.
Graph Embedding相关文献
Paper References with the implementation(s)
- AspEm
- AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks
- [paper]
- [Python]
- gat2vec
- gat2vec: Representation learning for attributed graphs
- [paper]
- [Python]
- FSCNMF
- FSCNMF: Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks
- [paper]
- [Python]
- SIDE
- SIDE: Representation Learning in Signed Directed Networks
- [paper]
- [Python]
- [Site]
- AWE
- Anonymous Walk Embeddings, ICML’18
- [paper]
- [Python]
- BiNE
- BiNE: Bipartite Network Embedding, SIGIR’18
- [paper]
- [Python]
- HOPE
- Asymmetric Transitivity Preserving Graph Embedding
- [KDD 2016]
- [Python]
- VERSE
- VERSE, Versatile Graph Embeddings from Similarity Measures
- [Arxiv] [[WWW 2018]]
- [Python]
- AGNN
- Attention-based Graph Neural Network for semi-supervised learning
- [ICLR 2018 OpenReview (rejected)]
- [Python]
- Hyperbolics
- Representation Tradeoffs for Hyperbolic Embeddings
- [Arxiv]
- [Python]
- DGCNN
- An End-to-End Deep Learning Architecture for Graph Classification
- [AAAI 2018]
- [Lua] [Python]
- structure2vec
- Discriminative Embeddings of Latent Variable Models for Structured Data
- [Arxiv]
- [Python]
- Decagon
- Decagon, Graph Neural Network for Multirelational Link Prediction
- [Arxiv] [SNAP] [[ISMB 2018]]
- [Python]
- Ohmnet
- Feature Learning in Multi-Layer Networks
- [Arxiv] [SNAP]
- [Python]
- SDNE
- Structural Deep Network Embedding
- [KDD 2016]
- [Python]
- STWalk
- STWalk: Learning Trajectory Representations in Temporal Graphs]
- [Arxiv]
- [Python]
- LoNGAE
- Learning to Make Predictions on Graphs with Autoencoders
- [Arxiv]
- [Python]
- RSDNE
- RSDNE: Exploring Relaxed Similarity and Dissimilarity from Completely-imbalanced Labels for Network Embedding., AAAI 2018
- [Matlab]
- FastGCN
- FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
- [Arxiv], [ICLR 2018 OpenReview]
- [Python]
- GEMSEC
- GEMSEC: Graph Embedding with Self Clustering, arXiv 2018
- [Python]
- diff2vec
- Fast Sequence Based Embedding with Diffusion Graphs, CompleNet 2018
- [Python]
- Poincare
- Poincaré Embeddings for Learning Hierarchical Representations, NIPS 2017
- [PyTorch] [Python] [C++]
- PEUNE
- PRUNE: Preserving Proximity and Global Ranking for Network Embedding, NIPS 2017
- [code]
- ASNE
- Attributed Social Network Embedding, arxiv’17
- [arxiv] [Python]
- GraphWave
- Spectral Graph Wavelets for Structural Role Similarity in Networks,
- [arxiv], [ICLR 2018 OpenReview]
- [Python]
- StarSpace
- StarSpace: Embed All The Things!, arxiv’17
- [code]
- proNet-core
- Vertex-Context Sampling for Weighted Network Embedding, arxiv’17
- [arxiv] [code]
- struc2vec
- struc2vec: Learning Node Representations from Structural Identity, KDD’17
- [Python]
- ComE
- Learning Community Embedding with Community Detection and Node Embedding on Graphs, CIKM’17
- [Python]
- M-NMF
- Community Preserving Network Embedding, AAAI’17
- [Python]
- GraphSAGE
- Inductive Representation Learning on Large Graphs, NIPS’17
- [arxiv] [TF] [PyTorch]
- ICE
- ICE: Item Concept Embedding via Textual Information, SIGIR’17
- [demo] [code]
- metapath2vec
- metapath2vec: Scalable Representation Learning for Heterogeneous Networks, KDD’17
- [paper] [project website]
- GCN
- Semi-Supervised Classification with Graph Convolutional Networks, ICLR’17
- [arxiv] [Python Tensorflow]
- GAE
- Variational Graph Auto-Encoders, arxiv
- [arxiv] [Python Tensorflow]
- CANE
- CANE: Context-Aware Network Embedding for Relation Modeling, ACL’17
- [paper] [Python]
- TransNet
- TransNet: Translation-Based Network Representation Learning for Social Relation Extraction, IJCAI’17
- [Python Tensorflow]
- cnn_graph
- Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering, NIPS’16
- [Python]
- ConvE
- Convolutional 2D Knowledge Graph Embeddings, arxiv
- [source]
- node2vec
- node2vec: Scalable Feature Learning for Networks, KDD’16
- [arxiv] [Python] [Python-2] [Python-3] [C++]
- DNGR
- Deep Neural Networks for Learning Graph Representations, AAAI’16
- [Matlab] [Python Keras]
- HolE
- Holographic Embeddings of Knowledge Graphs, AAAI’16
- [Python-sklearn] [Python-sklearn2]
- ComplEx
- Complex Embeddings for Simple Link Prediction, ICML’16
- [arxiv] [Python]
- MMDW
- Max-Margin DeepWalk: Discriminative Learning of Network Representation, IJCAI’16
- [paper] [Java]
- planetoid
- Revisiting Semi-supervised Learning with Graph Embeddings, ICML’16
- [arxiv] [Python]
- PowerWalk
- PowerWalk: Scalable Personalized PageRank via Random Walks with Vertex-Centric Decomposition, CIKM’16
- [code]
- LINE
- LINE: Large-scale information network embedding, WWW’15
- [arxiv] [C++] [Python TF] [Python Theano/Keras]
- PTE
- PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks, KDD’15
- [C++]
- GraRep
- Grarep: Learning graph representations with global structural information, CIKM’15
- [Matlab]
- KB2E
- Learning Entity and Relation Embeddings for Knowledge Graph Completion, AAAI’15
- [paper] [C++] [faster version]
- TADW
- Network Representation Learning with Rich Text Information, IJCAI’15
- [paper] [Matlab]
- DeepWalk
- DeepWalk: Online Learning of Social Representations, KDD’14
- [arxiv] [Python] [C++]
- GEM
- Graph Embedding Techniques, Applications, and Performance: A Survey
- [arxiv] [Python]
Paper References
MetaGraph2Vec, MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding
PinSAGE, Graph Convolutional Neural Networks for Web-Scale Recommender Systems
Curriculum Learning for Heterogeneous Star Network Embedding via Deep Reinforcement Learning, WSDM '18
Adversarial Network Embedding, arxiv
Role2Vec, Learning Role-based Graph Embeddings
edge2vec, Feature Propagation on Graph: A New Perspective to Graph Representation
Learning
MINES, Multi-Dimensional Network Embedding with Hierarchical Structure
Walk-Steered Convolution for Graph Classification
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
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
WWW-18 Tutorial Representation Learning on Networks, WWW’18
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