文件名称:
A Comprehensive Survey on Graph Neural NETWORKS.pdf
开发工具:
文件大小: 1mb
下载次数: 0
上传时间: 2020-02-27
详细说明：Deep learning has revolutionized many machine
learning tasks in recent years, ranging from image classification
and video processing to speech recognition and natural language
understanding. The data in these tasks are typically represented
in the Euclidean space. However, there is an increasing number
of applications where data are generated from non-Euclidean domains
and are represented as graphs with complex relationships
and interdependency between objects. The complexity of graph
data has imposed significant challenges on existing machine
learning algorithms. Recently, many studies on extending deep
learning approaches for graph data have emerged. In this survey,
we provide a comprehensive overview of graph neural networks
(GNNs) in data mining and machine learning fields. We propose
a new taxonomy to divide the state-of-the-art graph neural
networks into four categories, namely recurrent graph neural
networks, convolutional graph neural networks, graph autoencoders,
and spatial-temporal graph neural networks. We further
discuss the applications of graph neural networks across various
domains and summarize the open source codes, benchmark data
sets, and model evaluation of graph neural networks. Finally,
we propose potential research directions in this rapidly growing
field.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
相关说明
- 本站资源为会员上传分享交流与学习,如有侵犯您的权益,请联系我们删除.
- 本站是交换下载平台，提供交流渠道，下载内容来自于网络，除下载问题外，其它问题请自行百度。
- 本站已设置防盗链，请勿用迅雷、QQ旋风等多线程下载软件下载资源，下载后用WinRAR最新版进行解压.
- 如果您发现内容无法下载，请稍后再次尝试；或者到消费记录里找到下载记录反馈给我们.
- 下载后发现下载的内容跟说明不相乎，请到消费记录里找到下载记录反馈给我们，经确认后退回积分.
- 如下载前有疑问，可以通过点击"提供者"的名字，查看对方的联系方式，联系对方咨询.
