2018-07-13

Graph Convolutional Network(GCN)微信公众号文章

Graph Convolutional Networks | Thomas Kipf | PhD Student @ University of Amsterdam
https://tkipf.github.io/graph-convolutional-networks/#fn3

图卷积网络(Graph Convolutional networks, GCN) 简述
https://zhuanlan.zhihu.com/p/38612863

Graph Convolutional Networks (GCNs) 简介 - AHU-WangXiao - 博客园
https://www.cnblogs.com/wangxiaocvpr/p/8059769.html

如何理解 Graph Convolutional Network(GCN)? - 知乎
https://www.zhihu.com/question/54504471

卷积神经网络不能处理“图”结构数据?这篇文章告诉你答案 | 雷锋网
https://www.leiphone.com/news/201706/ppA1Hr0M0fLqm7OP.html

深度学习在graph上的使用
https://zhuanlan.zhihu.com/p/27216346

专知 洛桑理工:Graph上的深度学习报告(附PPT下载)
https://mp.weixin.qq.com/s/Jt6CjMqNFEXWoL5pkLeVyw

新智元 Graph 卷积神经网络:概述、样例及最新进展
https://mp.weixin.qq.com/s/ZsnuY2ffUPbmCbBG-MnSyA

香港中大-商汤科技联合实验室AAAI录用论文详解:ST-GCN时空图卷积网络模型 https://mp.weixin.qq.com/s/GEbEDI-VDHPxCDW9SO7jtA

如何理解 Graph Convolutional Network(GCN)? - 知乎
https://www.zhihu.com/question/54504471

AAAI 2018 | 时空图卷积网络:港中文提出基于动态骨骼的行为识别新方案
https://mp.weixin.qq.com/s/uxawHWsVXMNOTLNthAL0vg

实现
tkipf/gcn: Implementation of Graph Convolutional Networks in TensorFlow
https://github.com/tkipf/gcn

yysijie/st-gcn: Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch
https://github.com/yysijie/st-gcn

浅析图卷积神经网络 - 简书
https://www.jianshu.com/p/89fbed65cd04

《Graph Learning》| 图传播算法(上) - 简书
https://www.jianshu.com/p/53b4a3584199

《Graph learning》| 图传播算法(下) - 简书
https://www.jianshu.com/p/e7fb897b1d09

Advances in Deep Learning on Graphs
链接:https://pan.baidu.com/s/1mTqZQY85Oi0sW2jR7mohMA
密码:yfku

Semi-Supervised Classification with Graph Convolutional Networks
https://openreview.net/pdf?id=SJU4ayYgl

Modeling Relational Data with Graph Convolutional Networks
https://arxiv.org/abs/1703.06103

Inductive Representation Learning on Large Graphs
https://arxiv.org/abs/1706.02216

[1801.07606] Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning
https://arxiv.org/abs/1801.07606

Eilene/spatio-temporal-paper-list: Spatio-temporal modeling 论文列表(主要是graph convolution相关)
https://github.com/Eilene/spatio-temporal-paper-list

How powerful are Graph Convolutions? (review of Kipf & Welling, 2016)
https://www.inference.vc/how-powerful-are-graph-convolutions-review-of-kipf-welling-2016-2/

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