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Can GraphSAGE be applied to characterize vrp data?

My scene is as follows: (1) Suppose there are 10000 vrp graph, each graph contains 100 nodes and each node is featured by its coordinates, i.e. (x,y) (2) My goal is to use these data to train a ...
jinkun Dong's user avatar
1 vote
0 answers
26 views

Graph Clustering algorithms when both nodes *and* edges have features (numerical, categorical and potentially even temporal!)

I'm trying to figure out how much complexity I can get away with and am looking for model recommendations. I have transactional data on hand - the features being customer id, customer balance, ...
MergeMonster's user avatar
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What is the prior mu in Heterogeneous Graph Transformer?

I am reading https://arxiv.org/pdf/2003.01332.pdf and do not understand what the prior (\mu) is supposed to be. I also found their implementation on github, but it is still not clear to me. For ...
Servus's user avatar
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Model Performance not improving

I am currently working with a GNN (a Graph attention Model) based model and the main task is to do Graph prediction. My model doesnot improve its performance when I change the number of heads or the ...
Susan's user avatar
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1 vote
1 answer
142 views

Trouble Training GNN for Binary Node Classification Task

I am using a GNN to solve a problem in which I have a query target and an undirected graph. My goal is to emit a subset of nodes in the graph (via a node-wise binary prediction) whose features sum to ...
mt_'s user avatar
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1 answer
127 views

Matching nodes in two directed graphs

How to match a node of graph X with the same node in graph G if: Every node has only one feature: text string, and Nodes in different graphs are considered to be equal if: ...
dokondr's user avatar
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0 answers
328 views

My model is not learning

I am using the ogb molhiv dataset for graph classification, I imported the data and created the DataLoader following the ogb documentation. The data is composed of 41127 graphs and there are 2 classes....
edak's user avatar
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2 answers
34 views

Same code vastly different accuracies

I am working on a node classification model, My friend implemented a simple 2 layer GCN and got an accuracy of 62%, I implemented the same code and got an accuracy of 50% we are both working on google ...
edak's user avatar
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1 vote
0 answers
95 views

Graph Neural Network | How node embeddings are learned from several graphs?

I am reading paper on MEGnet which is a GNN. The objective is that we have several molecules that share same elements such as molecules $C0_2$ and $COOH$ share $C$ and $O$. Now if we learn the node ...
user0193's user avatar
  • 155
1 vote
1 answer
40 views

When an author says Features are the input to Machine Learning Model what does it mean?

I am reading an article about graph neural network and it is mentioned: In this step, we extract all newly update hidden states and create a final feature vector describing the whole graph. This ...
user0193's user avatar
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1 vote
1 answer
50 views

How to define similarity between nodes in original graph?

While there has been a lot of talk in how to define the similarity between nodes in the embedding space, but I don't seem to come across any talking about defining the similarity between nodes in the ...
Student's user avatar
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2 answers
2k views

What is the model architectural difference between transductive GCN and inductive GraphSAGE?

Difference of the model design. It seems the difference is that GraphSAGE sample the data. But what is the difference in model architecture.
CoderOnly's user avatar
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6 votes
1 answer
3k views

What is difference between transductive and inductive in GNN?

It seems in GNN(graph neural network), in transductive situation, we input the whole graph and we mask the label of valid data and predict the label for the valid data. But is seems in inductive ...
CoderOnly's user avatar
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