SINE
Network embedding algorithm
An implementation of a scalable method for learning node representations in complex networks
A PyTorch Implementation of "SINE: Scalable Incomplete Network Embedding" (ICDM 2018).
72 stars
9 watching
18 forks
Language: Python
last commit: over 1 year ago
Linked from 2 awesome lists
aaneasnedeep-learningdeepwalkdimensionality-reductiongensimgraph-embeddinggrarepmachine-learningnetwork-embeddingnetworkxnode-embeddingnode2vecpytorchsklearntadwtensorflowtorchunsupervised-learningwalklets
Related projects:
Repository | Description | Stars |
---|---|---|
daokunzhang/sine | This project provides an implementation of network embedding method SINE, designed to learn compact and informative node representations from incomplete networks. | 10 |
benedekrozemberczki/musae | Implementation of a method for generating node embeddings in graph data with attributed information | 159 |
benedekrozemberczki/tene | A sparsity-aware implementation of a deep learning algorithm for graph embedding with text information. | 73 |
benedekrozemberczki/grarep | An implementation of a method for learning graph representations from global structural information in a network | 63 |
benedekrozemberczki/role2vec | An implementation of a deep learning-based method for creating vector representations of nodes in a graph | 166 |
benedekrozemberczki/bane | A software implementation of a graph embedding algorithm | 86 |
benedekrozemberczki/boostedfactorization | An implementation of multi-level network embedding with boosted low-rank matrix approximation | 35 |
benedekrozemberczki/diff2vec | A reference implementation of Diffusion2Vec, a method for learning node embeddings from graph data. | 126 |
benedekrozemberczki/attentionwalk | An implementation of a deep learning algorithm to generate node embeddings in graphs | 320 |
benedekrozemberczki/m-nmf | An implementation of Community Preserving Network Embedding using deep learning and matrix factorization techniques | 120 |
benedekrozemberczki/gemsec | A reference implementation of graph embedding with clustering using deep learning techniques | 252 |
benedekrozemberczki/sgcn | An implementation of a deep learning algorithm for graph data | 268 |
benedekrozemberczki/asne | A software implementation of a method to reduce the dimensionality of attributed graphs | 82 |
benedekrozemberczki/simgnn | An implementation of SimGNN, a neural network approach to computing graph similarity | 759 |
benedekrozemberczki/feather | A reference implementation of a method for learning graph node embeddings from graph structure and node features | 45 |