Questions tagged [graph-neural-network]
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55 questions
5votes
1answer
60views
Choosing NN architecture for route correction
Can you help me choose a NN architecture that solves this kind of problem: A route, meaning a sequence of coordinates (e.g. [(34.1, 52.3),(34.101, 52.301), ... ]), ...
3votes
1answer
79views
Pytorch mat1 and mat2 shapes cannot be multiplied (131072x12 and 64x32)
I have a multivariate time series forecasting model that originally used dilated temporal convolution for temporal dependencies extraction that i tried to replace with multi head self-attention with ...
1vote
0answers
13views
Could I use GCN get nodes structual embedding without training?
Now, I want to get nodes' structual embedding, use DeepWalk or Node2Vec couldn't get same vector even they have same structure. then I use GCN which could get same vector without training. So I want ...
0votes
0answers
43views
How to handle imbalanced edge weights in a graph for node embedding and edge weight prediction?
I have an undirected weighted graph where the edge weights represent probabilities. The majority of the edge weights are 1 (which are 7 times more frequent than the second major group of weights). I'm ...
0votes
1answer
14views
Improving Data Sets by Adding New Nodes
I have an idea for adding new nodes into a directed graph to achieve a numerically stable graph Fourier transform for signal analysis in the graph domain. To assess its efficiency, I am looking for ...
- 103
0votes
0answers
5views
Paper GAMENet (2019): what is the intuition behind fusing two Graph Convolution Networks?
In paper GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination (Shang et al, 2019), the authors leveraged two graphs, where each node is a (unique) medication code. These ...
- 111
0votes
0answers
60views
the features in cora dataset
Cora dataset contains a citation gragh which also contains feature vectors for each paper. The size of the feature vectors is 1433 (corresponding to unique words). Feature vectors contain binary ...
- 123
2votes
0answers
20views
spectral gnn forward pass
Following the article: A Practical Guide to Graph Neural Networks: https://arxiv.org/abs/2010.05234 Suppose our graph has $N$ nodes and Laplacian $L = UDU^T$. Let $\Theta$ denote a filter. Let $f_{k}$ ...
1vote
1answer
35views
How can a citation dataset (like Cora) have strongly connected components?
This website https://snap.stanford.edu/data/cit-HepPh.html shows that the High-energy physics citation network has strongly connected components and it's driving me crazy. A SCC would mean that you ...
1vote
1answer
42views
Asynchronous Training of Deep Learning Models
I am thinking of how would it be if I can create asynchronous forward function in sub-class of nn.Module . When I came across architecture in attached image, I felt that it would be faster if we could ...
1vote
1answer
309views
What're the standard ways of padding data for GNNs?
I am working on materials property prediction using GNNs with torch_geometric. Each data in my dataset has different number of feature vectors x, edge_index vectors ...
0votes
0answers
264views
Convert specific domain knowledge text to a knowledge graph
As part of this semester assignment , I'm working on a project that aims to to represent the knowledge in "PMBOK 6th edition, section 11: Project Risk Management (page 395 -> 458)" and the knowledge ...
0votes
1answer
1kviews
Implementation of Graph Neural Network for Image Classification
I'm currently working on a project where I want to utilize Graph Neural Networks (GNNs) for image classification tasks. However, I'm facing difficulties in understanding how to implement GNNs ...
1vote
1answer
345views
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 ...
- 11
0votes
1answer
48views
What are effective ways to merge different parts of a document to form a single document?
I have a dataset where I have 3 different columns (Title, Keyword and Abstract) representing a document. I have to build a text classification model using TextGCN, where documents and words will be ...
