Questions tagged [graph-neural-networks]

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

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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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26 views

How do I interpret the following parameters as a network

I have a background in OR and I am new to AI. I know the basics and I currently try to understand the article "Learning Combinatorial Optimization Algorithms over Graphs". So far I ...
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15 views

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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9 views

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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1answer
34 views

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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1answer
27 views

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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0answers
10 views

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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2answers
80 views

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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111 views

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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946 views

Machine learning with graph as input and output

In my application, I have inputs and outputs that could be represented as graphs. I have a number of acceptable pairs of input and output graphs. I want to use these to train a model. I am looking ...