Questions tagged [gnn]
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12 questions
0 votes
0 answers
18 views
GNN Based unsupervised Anomaly Detection for Heterogeneous Graphs
I am working on a project where I am doing Unsupervised Anomaly Detection on employee expenses on HCP transfer Of Value. I am trying to use Graph Neural Network to detect anomalies with proper ...
1 vote
0 answers
29 views
Preference learning for collaborative scheduling
I am working on a project of integrating the preferences of the workers into a schedule, I mean we won’t only satisfy the systematic constraints but also users preferences as constraints, so we are ...
- 11
1 vote
0 answers
61 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, ...
- 11
2 votes
1 answer
405 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 ...
- 21
0 votes
1 answer
182 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: ...
- 295
0 votes
0 answers
346 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....
- 13
1 vote
2 answers
63 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 ...
- 13
1 vote
0 answers
146 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 ...
- 165
1 vote
1 answer
56 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 ...
- 165
2 votes
1 answer
78 views
How to define similarity between nodes in original graph?
While there has been a lot of talk about defining the similarity between nodes in the embedding space, I don't seem to come across any talking about defining the similarity between nodes in the ...
- 421
1 vote
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.
- 721
7 votes
1 answer
4k 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 ...
- 721