Questions tagged [gnn]

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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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Building a graphic neural network (GNNs) model from my own dataset (tabular dataset)

I am intended to build a GNN. I am using my own dataset (tabular dataset), so to build a graph I can't use benchmark datasets as I have my own dataset. How can I build a graph first and then build a ...
Abdullah's user avatar
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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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how to find out input data, its structure and how to achieve them on graph machine learning model?

I'm a newbie in graph machine learning and apologize if my question is silly. There is a model suggested in some paper for inductive link prediction, I need to use that model on my custom graph but I ...
Fateme's user avatar
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277 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
32 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
69 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
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1 answer
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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
38 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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1 vote
2 answers
1k 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.
DunkOnly's user avatar
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1 answer
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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 ...
DunkOnly's user avatar
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