# Questions tagged [graph-neural-networks]

For questions related to graph neural networks, which are artificial neural networks applied to graphs.

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### What is the reason behind using node embeddings?

I was reading Chapter 3 from the following book (here) on graph representation learning. The chapter is about node embeddings. Question: What is the point of using node embeddings? Do we use them: to ...
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### What are examples of node 'features' in graph networks?

Context: I was reading Chapter 3 in the following book (here) about graph representation learning. Before I get to node embeddings, I wanted to make sure that I do understand what is meant by the ...
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### How Graph Convolutional Neural Networks forward propagate?

In the basic variant of GCN we have the following: Here we aggregate the information from the adjacent node and pass it to a neural network, then transform our own information and add them all. But ...
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### What is the best resources to learn Graph Convolutional Neural Networks?

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 ...
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### How to design a graph neural network to predict the forces in truss elements of a space frame?

I am trying to create a Graph NN that will be able to predict the forces in truss elements of a space frame. The input for the NN will be a graph, where the nodes represent the nodes of the spaceframe....
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### How to learn how to select a subgraph via reinforcement learning?

I have the following problem. I am given a graph with a lot (>30000) nodes. Nodes are associated with a low (<10)-dimensional feature vector, and edges are associated with a low (<10)-...
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### How can feedforward neural networks act as contraction maps?

In graph neural networks, the Banach fixed-point theorem and Jacobi method it is described that the transition from one state to another be defined by a contraction map with a fixed-point. The autor ...
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### How do CNNs or RNNs "stack the feature of nodes by a specific order"?

I am trying to understand the following statement taken from the paper Graph Neural Networks: A Review of Methods and Applications (2019). Standard neural networks like CNNs and RNNs cannot handle ...
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### Understanding the node information score in the paper "Hierarchical Graph Pooling with Structure Learning"

The paper Hierarchical Graph Pooling with Structure Learning (2019) introduces a distance measure between: a graph's node-representation matrix $\text{H}$, and an approximation of this constructed ...
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### What are some conferences for publishing papers on graph convolutional networks?

What are some conferences for publishing papers on graph convolutional networks?
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### How to estimate the convolutional representation of a graph from its similarity to other graph convolutional representation?

Suppose we have two graphs A and B disconnected to each other (let's say 2-hops each), within a larger graph. If the convolutional representation of graph A is known, is it possible to estimate the ...
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### How should I deal with multi-dimensional tensors for nodes in a graph convolution network?

How to work with GCN when the features of each node is not a 1D vector? For example, if the graph has N nodes and each node has features of the form $C \times D \times E$. Also, is there an open-...
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### Is there an open-source implementation for graph convolution networks for weighted graphs?

Currently, I'm using a Python library, StellarGraph, to implement GCN. And I now have a situation where I have graphs with weighted edges. Unfortunately, StellarGraph doesn't support those graphs I'm ...
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### Are there neural networks that accept graphs or trees as inputs?

As far I know, the RNN accepts a sequence as input and can produce as a sequence as output. Are there neural networks that accept graphs or trees as inputs, so that to represent the relationships ...
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### What is non-Euclidean data?

What is non-Euclidean data? Here are some sub-questions Where does this type of data arise? I have come across this term in the context of geometric deep learning and graph neural networks. ...
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### What is a graph neural network?

What is a graph neural network (GNN)? Here are some sub-questions How is a GNN different from a NN? How exactly is a GNN related to graphs? What are the components of a GNN? What are the inputs and ...