Relational inductive biases, deep learning, and graph networks 论文导读，DeepMind图网络

时间 2020-12-30

标签图网络人工智能深度学习 relation DeepMind 栏目 Google 繁體版

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推荐理由 Relational inductive biases, deep learning, and graph networks 标题：《关系归纳偏好、深度学习和图网络》简述 DeepMind联合谷歌大脑、MIT等机构的27位作者发表重磅论文，提出“图网络”（Graph network, GN）。论文由27位作者联合发表 DeepMind作为行业标杆，其动向一

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1. 《Relational inductive biases, deep learning, and graph networks》图网络论文解读
2. Relational inductive biases, deep learning, and graph networks
3. 《Relational inductive biases, deep learning, and graph networks》论文解读（转载）
4. 读书笔记7：Relational inductive biases, deep learning, and graph networks
5. GNN新作《Relational inductive biases，deep learning，and graph networks》读书笔记
6. 论文笔记11：Relational inductive biases, deep learning, and graph networks翻译笔记
7. GNN初学笔记（一）—— Relational inductive biases, deep learning, and graph networks简要解析
8. 图卷积网络、图神经网络必读论文
9. 图神经网络论文阅读(六) GRAPH ATTENTION NETWORKS，ICLR2018
10. Learning about Graph Network

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