DGCNN
Graph classifier
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.
Code for "M. Zhang, Z. Cui, M. Neumann, and Y. Chen, An End-to-End Deep Learning Architecture for Graph Classification, AAAI-18".
174 stars
8 watching
44 forks
Language: Matlab
last commit: over 6 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
deepgraphlearning/gmnn | A software framework that integrates statistical relational learning and graph neural networks for semi-supervised object classification and unsupervised node representation learning. | 401 |
benedekrozemberczki/seal-ci | A PyTorch implementation of a semi-supervised graph classification model that learns hierarchical representations from labeled and unlabeled graph data. | 208 |
gasteigerjo/ppnp | This project provides implementations of graph neural network models for personalized page rank task | 319 |
hongyanggao/lgcn | An implementation of learnable graph convolutional networks for efficient graph processing | 46 |
benedekrozemberczki/gam | An implementation of a graph classification model using structural attention and PyTorch | 268 |
benedekrozemberczki/mixhop-and-n-gcn | A deep learning framework implementation of higher-order graph convolutional architectures and their applications | 402 |
benedekrozemberczki/sgcn | An implementation of a deep learning algorithm for graph data | 268 |
lonl/cdbn | An implementation of a neural network architecture for image classification using convolutional and belief propagation techniques. | 35 |
dmlc/gnnlens2 | An interactive visualization tool for graph neural networks | 239 |
yuetan031/fedstar | This project implements a federated learning algorithm for non-IID graph classification tasks by leveraging structural knowledge sharing. | 58 |
zhengwang100/rect | A deep learning framework for graph representation learning with partially labeled data | 18 |
liqimai/gcn | An implementation of graph convolutional networks for semi-supervised learning in Python using TensorFlow and other libraries. | 45 |
mdeff/cnn_graph | An implementation of convolutional neural networks on graphs using spectral filtering | 1,339 |
delta2323/gb-gnn | Analyzes and optimizes the performance of graph neural networks using gradient boosting and various aggregation models. | 13 |
matlab-deep-learning/abnormal-eeg-signal-classification-using-cnns | Develops and trains a deep neural network to classify EEG signals as normal or abnormal | 48 |