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戴晨阳/graphsage-simple

Simple reference implementation of GraphSAGE.

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戴晨阳/style-transfer

An implementation of "A Neural Algorithm of Artistic Style" by L. Gatys, A. Ecker, and M. Bethge. http://arxiv.org/abs/1508.06576.

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戴晨阳/ImageDenoisingGAN

Image Denoising with Generative Adversarial Network

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戴晨阳/diffpool

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戴晨阳/GCN-DIFFPOOL

this is a implementation of gcn model with DIFFPOOL layer in tensorflow

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戴晨阳/cogdl

CogDL: An Extensive Toolkit for Deep Learning on Graphs

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戴晨阳/text_gcn

Graph Convolutional Networks for Text Classification. AAAI 2019

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戴晨阳/gcn_metric_learning

Metric Learning with Graph Convolutional Neural Networks

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戴晨阳/spectral_graph_convnets

PyTorch implementation of spectral graph ConvNets, NIPS’16

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戴晨阳/cnn_graph

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

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戴晨阳/GraphSAGE

Representation learning on large graphs using stochastic graph convolutions.

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戴晨阳/Keras-FasterRCNN

keras implementation of Faster R-CNN

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戴晨阳/MyCSDN_Blog

some naive code

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戴晨阳/GAT

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

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戴晨阳/pyGAT

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

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戴晨阳/gcn_mnist

Use GCN to classify Mnist

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戴晨阳/T-GCN

Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method

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戴晨阳/CapsGNN

A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

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戴晨阳/ML-GCN

PyTorch implementation of Multi-Label Image Recognition with Graph Convolutional Networks, CVPR 2019.

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戴晨阳/pygcn

Graph Convolutional Networks in PyTorch