All Projects → nate-russell → Network-Embedding-Resources

nate-russell / Network-Embedding-Resources

Licence: MIT license
Network Embedding Survey and Resources

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NetworkEmbedding

This repo is intended as a reference page for network embedding literature and code. I will be adding

  • links to network embedding papers
  • links to implementations of network embedding algorithms
  • links to data sets used in network embedding literature
  • links to reviews / presentations on network embedding

What is Network Embedding? Why should we care?

![](/Images/Chang et al KDD 2015.png) The Above figure comes from Chang et all KDD 2015

Table

Last Updated (2/14/17)

Paper Year # of Citations Weighted Directed Typed Typed Nodes
Distributed Large-scale Natural Graph Factorization 13 29 ? ? ? ?
Translating Embeddings for Modeling Multi-relational Data (TransE) 13 234
DeepWalk: Online Learning of Social Representations 14 158
Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge Bases (Tatec) 15 7
Holographic Embeddings of Knowledge Graphs (HOLE) 15 10
Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks 15 11
GraRep: Learning Graph Representations with Global Structural Information 15 15
Deep Graph Kernels 15 16
Heterogeneous Network Embedding via Deep Architectures 15 25
PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks 15 30
LINE: Large-scale Information Network Embedding 15 90
A General Framework for Content-enhanced Network Representation Learning (CENE) 16 0
Variational Graph Auto-Encoders (VGAE) 16 0
PROSNET: INTEGRATING HOMOLOGY WITH MOLECULAR NETWORKS FOR PROTEIN FUNCTION PREDICTION. 16 0
Large-Scale Embedding Learning in Heterogeneous Event Data (HEBE) 16 0
AFET: Automatic Fine-Grained Entity Typing by Hierarchical Partial-Label Embedding 16 0
Deep Neural Networks for Learning Graph Representations (DNGR) 16 1
subgraph2vec: Learning Distributed Representations of Rooted Sub-graphs from Large Graphs 16 2
Walklets: Multiscale Graph Embeddings for Interpretable Network Classification 16 2
Asymmetric Transitivity Preserving Graph Embedding (HOPE) 16 3
Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding (PLE) 16 6
Semi-Supervised Classification with Graph Convolutional Networks (GCN) 16 7
Revisiting Semi-Supervised Learning with Graph Embeddings (Planetoid) 16 10
Structural Deep Network Embedding 16 12
node2vec: Scalable Feature Learning for Networks 16 27

Ontology

(In progress) Network diagram of network embedding research papers. Intended to help people grab a quick lay of the network embedding landscape.

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