Answers.Body: <p>There is also the proto-book <a href="https://arxiv.org/pdf/2104.13478.pdf" rel="nofollow noreferrer">Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges</a> (2021), written by some of the experts on the topic. The book does not focus only on graphs and graph neural networks (GNNs), but also covers manifolds, geodesics, and other mathematical concepts related to geometric deep learning and other GDL models.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-11-29T12:36:03.657Z
Answers.LastActivityDate: 2021-11-29T12:36:03.657Z
Answers.UserDisplayName: nbro
Answers.Body: <p>I believe <a href="http://web.archive.org/web/20201126231906/https://www.cs.mcgill.ca/%7Ewlh/grl_book/" rel="nofollow noreferrer"><em>Graph Representation Learning</em></a> book by William L. Hamilton is a great resource to start</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-11-07T21:16:49.687Z
Answers.Text: thank u for this suggestion. which pages (part) of this book is about GCN?
Answers.UserDisplayName: Morteza Jalambadani
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Answers.CreationDate: 2020-11-05T20:45:28.783Z
Answers.LastActivityDate: 2021-01-15T11:24:24.827Z
Answers.LastEditDate: 2021-01-15T11:24:24.827Z
Answers.UserDisplayName: gcorso
Body: <p>For the past few days, I am trying to learn graph convolutional networks. I saw some of the lectures on youtube. But I can not able to get any clear concept of how those networks are trained. I have a vague understanding of how to perform convolution, but I can not understand how we train them. I want a solid mathematical understanding of graph convolutional networks. So, can anyone please suggest me how to start learning graph convolutional network from start to expert level?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-07-24T19:51:49.110Z
Comments.Text: See [What is a graph neural network?](https://ai.stackexchange.com/q/11169/2444).
Comments.UserDisplayName: nbro
Tags: <resource-request><geometric-deep-learning><graph-neural-networks>
Title: What is the best resources to learn Graph Convolutional Neural Networks?
UserDisplayName: Swakshar Deb
ThreadText: # What is the best resources to learn Graph Convolutional Neural Networks?
  
  (Asked by: username_0 on 2020-07-22)
  
  For the past few days, I am trying to learn graph convolutional networks. I saw some of the lectures on youtube. But I can not able to get any clear concept of how those networks are trained. I have a vague understanding of how to perform convolution, but I can not understand how we train them. I want a solid mathematical understanding of graph convolutional networks. So, can anyone please suggest me how to start learning graph convolutional network from start to expert level?
  
  **Tags:** resource-request, geometric-deep-learning, graph-neural-networks
  > **Comments:**
  > **username_1**: See [What is a graph neural network?](https://ai.stackexchange.com/q/11169/2444).  
  
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  ## 2 answers
  
  ### Answer by username_2 on 2020-11-05. Score: 3 | Accepted answer
  
  I believe [*Graph Representation Learning*](http://web.archive.org/web/20201126231906/https://www.cs.mcgill.ca/%7Ewlh/grl_book/) book by William L. Hamilton is a great resource to start
  
  > **Comments:**
  > **username_3**: thank u for this suggestion. which pages (part) of this book is about GCN?  
  
  ---
  
  ### Answer by username_1 on 2021-11-29. Score: 1
  
  There is also the proto-book [Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges](https://arxiv.org/pdf/2104.13478.pdf) (2021), written by some of the experts on the topic. The book does not focus only on graphs and graph neural networks (GNNs), but also covers manifolds, geodesics, and other mathematical concepts related to geometric deep learning and other GDL models.
  
  
  ---
  
  