Implementation of Planar Graph Convolutional Networks in TensorFlow
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Updated
May 2, 2017 - Python
Implementation of Planar Graph Convolutional Networks in TensorFlow
Chainer implementation of 'Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering' (https://arxiv.org/abs/1606.09375)
⚡ Using deep learning (MLP, CNN, Graph CNN) to classify text in TensorFlow.
Representation learning on large graphs using stochastic graph convolutions.
Non-maximum suppression for object detection in a neural network
TensorFlow Implementation of Graph Convolutional Networks Examples
code for zhijiang cup about zero shot learning
Code for A GRAPH-CNN FOR 3D POINT CLOUD CLASSIFICATION (ICASSP 2018)
Graph Convolutional Networks in Chainer
MXNet implementation of Graph Convolutional Neural Networks
TensorFlow implementation of Deep Graph Infomax
Code for Graph Convolutional Matrix Factorization for Bipartite Edge Prediction
Dynamic Graph Convolutional Neural Network for 3D point cloud semantic segmentation
Graph Convolutional Neural Networks for Theano
A convenient wrapper to develop graph neural networks with Keras. Currently under development with the objective of integrating Networkx, Owlready2 and oneM2M for cognitive IoT.
Dating Documents using Graph Convolution Networks
Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders (IJCAI 2018)
Integrative Analysis of Patient Health Records and Neuroimages via Memory-based Graph Convolutional Network (ICDM 2018 full paper)
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