ppnp

Graph classifier

Implementations of a graph neural network model for personalized graph classification

PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)

GitHub

321 stars
10 watching
55 forks
Language: Jupyter Notebook
last commit: 9 days ago
Linked from 1 awesome list

deep-learninggcngnngraph-algorithmsgraph-classificationgraph-neural-networksmachine-learningpagerankpytorchtensorflow

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
benedekrozemberczki/appnp A PyTorch implementation of a graph neural network model that learns personalized node representations 367
benedekrozemberczki/gam An implementation of a graph classification model using structural attention and PyTorch 270
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/sgcn An implementation of a deep learning algorithm for graph data 270
muhanzhang/dgcnn A deep learning architecture for graph classification that extracts vertex features through propagation-based graph convolution and retains more node information than traditional sum pooling methods. 174
benedekrozemberczki/pdn An implementation of a neural network architecture designed to process graph-structured data 58
dawnranger/pytorch-agnn An implementation of an attention-based graph neural network in PyTorch for semi-supervised learning 146
benedekrozemberczki/capsgnn A PyTorch implementation of a graph neural network architecture 1,246
chingyaoc/ggnn.pytorch An implementation of a neural network architecture for processing graph-structured data and making predictions on nodes. 466
benedekrozemberczki/simgnn An implementation of SimGNN, a neural network approach to computing graph similarity 768
deepgraphlearning/gmnn A software framework that integrates statistical relational learning and graph neural networks for semi-supervised object classification and unsupervised node representation learning. 403
tensorflow/gnn Builds Graph Neural Networks on the TensorFlow platform using heterogeneous graphs and various machine learning techniques. 1,372
bupt-gamma/openhgnn An open-source toolkit for training and applying heterogeneous graph neural networks using PyTorch and the Deep Graph Library. 879
benedekrozemberczki/mixhop-and-n-gcn A deep learning framework implementation of higher-order graph convolutional architectures and their applications 403
hongyanggao/lgcn An implementation of learnable graph convolutional networks for efficient graph processing 46