SimGNN
Graph simulator
An implementation of SimGNN, a neural network approach to computing graph similarity
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
768 stars
11 watching
146 forks
Language: Python
last commit: about 2 years ago attention-mechanismdeep-learninggcngedgnngraph-attentiongraph-classificationgraph-convolutiongraph-edit-distancegraph-embeddinggraph-similaritymachine-learningnetwork-embeddingneural-networkpytorchsimgnnsklearntensor-networktensorflowwsdm
Related projects:
| Repository | Description | Stars |
|---|---|---|
| benedekrozemberczki/sgcn | An implementation of a deep learning algorithm for graph data | 270 |
| benedekrozemberczki/appnp | A PyTorch implementation of a graph neural network model that learns personalized node representations | 367 |
| benedekrozemberczki/capsgnn | A PyTorch implementation of a graph neural network architecture | 1,246 |
| benedekrozemberczki/clustergcn | A PyTorch implementation of a clustering algorithm for graph neural networks | 788 |
| benedekrozemberczki/gam | An implementation of a graph classification model using structural attention and PyTorch | 270 |
| benedekrozemberczki/pdn | An implementation of a neural network architecture designed to process graph-structured data | 58 |
| benedekrozemberczki/mixhop-and-n-gcn | A deep learning framework implementation of higher-order graph convolutional architectures and their applications | 403 |
| benedekrozemberczki/graphwaveletneuralnetwork | An implementation of a neural network for graph data, specifically designed to process wavelet transforms on graphs. | 577 |
| benedekrozemberczki/attentionwalk | An implementation of a deep learning algorithm to generate node embeddings in graphs | 322 |
| benedekrozemberczki/seal-ci | A PyTorch implementation of a semi-supervised graph classification model that learns hierarchical representations from labeled and unlabeled graph data. | 209 |
| benedekrozemberczki/pytorch_geometric_temporal | A PyTorch extension for building temporal graph neural networks with support for recurrent and attention-based models | 2,694 |
 snap-stanford/graphgym | A platform for designing and evaluating Graph Neural Networks (GNN) models | 1,738 |
| benedekrozemberczki/role2vec | An implementation of a deep learning-based method for creating vector representations of nodes in a graph | 167 |
| benedekrozemberczki/grarep | An implementation of a method for learning graph representations from global structural information in a network | 64 |
| benedekrozemberczki/sine | An implementation of a scalable method for learning node representations in complex networks | 72 |