Questions tagged [graph-neural-network]

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Validation accuracy does not increase for binary classification using GNN

I am trying to perform graph classification with GINConv model of GNN. I have tried everything from varying dropouts to weight decay (for L2 regularization), learning rate (1e-6 to 1e-3), batch ...
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10 views

Normalization in Neural Networks Regression in MATLAB

I have 20 samples for a regression fitting purpose in Neural Network Toolbox (nnstart, nftool) in MATLAB . I have 3 inputs of 20 samples each (3 X 20 ) and 1 output (3 X 20, as the output number is ...
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20 views

Optimisation of neural networks

Do neural networks get optimized by trial and error, by data scientists, or is there some way of optimizing values through accurate mathematical equations?
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41 views

What are latent representations?

I am reading some research papers about graph convolutional neural networks and I have seen the term "latent representations" used a lot. For instance, "the model was able to learn ...
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1answer
18 views

Understanding Node Embeddings

I have only just started to look into graph neural networks and I am a little confused on the node embedding process. Here is my understanding, please let me know if i misunderstood: Given unlabelled ...
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13 views

How to classify hierarchical feature?

Assume that I have this data set (a taxonomy of parent-child features) ...
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2answers
14 views

Spectral Networks and Deep Locally Connected Networks on Graphs

I’m reading the paper Spectral Networks and Deep Locally Connected Networks on Graphs and I’m having a hard time understanding the notation shown in the picture below (the scribbles are mine): ...
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19 views

Dying gradient issue in Graph Neural Networks

I am using Pytorch-Geometric library to implement a Graph Convolutional Layer(GCN) followed by few linear layers for a prediction task. But after training on graphs with np. of nodes being 10K and no. ...
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1answer
24 views

What is a good approach for embedding both textual and spatial features for document classification?

I am working on a document classifier that can perform the classification based on the document structure as well. My plan is to get the word embedding as well as the word coordinates and somehow ...
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20 views

(Graph Convolutional Network (GCN) based recommender system maintenance issue [closed]

I have built an item-item recommender model using (Graph Convolutional Network (GCN) for an E-commerce website. Could you please help me with the maintenance of the model. How often should I retrain ...
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23 views

Unstable Training when combining Graph Neural Networks for Graph Classification Tasks

I have been combining Graph Convolutional Layers and Graph Pooling layers to define a neural network architecture for Graph Classification tasks. Specifically, using the Graph Convolutional Layer ...
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20 views

Machine learning on graphs

I'm looking for some method/model to help me with my current problem: I have a geometry, consisting of points, and eges. For each point I take information about itself and its neighbours. For now I ...
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26 views

Derivative of activation function calculating the delta of the bias returns always 0

Right now I'm constructing a neural network using a graph (as an assignment). And I bumped up to the problem where I needed to calculate the delta of bias for backpropagation. The thing is, if bias is ...
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Force Matching in Coarse Grained Molecular Dynamics with Jax - Forces do not match when neglecting energy loss

I am currently exploring force matching approaches for molecular dynamic simulations. As I am still in an exploration state, I'd tried investigated Force Matching Neural Network Colab Notebook ...
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1answer
67 views

From Labels to Graph: what machine learning approaches to use?

Imagine a world where we have places (e.g., cities, restaurants, national parks, etc.) but no roads connecting them. Our objective is to build roads connecting any two places while going through some ...
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57 views

HinSAGE link existence prediction?

From the demo of HinSAGE link prediction I’ve understood that the model can predict the label of a link between two nodes. I’m looking to know if a link should be existing (binary). For example, let’s ...
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14 views

What is the contraction map constraint in the context of Graph Neural Nets?

In this paper https://arxiv.org/pdf/1511.05493.pdf (GATED GRAPH SEQUENCE NEURAL NETWORKS,2016), it is stated that in a Graph Neural network initialising hidden states is not required, as 'In GNNs, ...
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110 views

What are the differences between Knowledge Graph Embeddings (KGE) and Graph Neural Network (GNN)

From page 3 of this paper Knowledge Graph Embeddings and Explainable AI, they mentioned as below: Note that knowledge graph embeddings are different from Graph Neural Networks (GNNs). KG embedding ...
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13 views

Multiple sizes and types of Inputs for a NN

I have multiple inputs for a Neural Network and a regression problem. The first input is a Adjacency matrix, the two other are one hot encodings(or binary). I am using the Flatten layer for each of ...
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22 views

Is there any inductive Graph Variational Auto Encoder?

I have been reading about how we can model a Variational AutoEncoder (VAE) into a Graph Variational AutoEncoder (GVAE) where the decoder reconstructs the adjacency matrix. I presume that this approach ...
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1answer
43 views

Knowledge Graph as an input to a neural network

I want to create a neural network that takes as an input a knolwedge subgraph(different types of nodes and different types of edges) to predict some properties. For instance an input in the graph can ...
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20 views

Graph Neural Network - Node and Global Properties

I am trying to work with Graph neural networks. I am trying to use the 3d coordinates and some othe things related to those positions as features. However the whole system also has some global ...
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1answer
65 views

Isn't graph embedding a step back from non-euclidean space?

As I understand, we use graph embedding to make a euclidean representation of non-euclidean structure - graph. Does it mean that conceptually we just take a step back to, may be, more complex, but ...
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1answer
69 views

How does graph classification work with graph neural networks

I am reading the paper The Graph Neural Network Model by Scarselli et al. I understand how node classification works. I am having trouble understanding how graph classification works however. In ...
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8 views

Deep Graph tutorial, visualization not displaying

I am following this Deep Graph tutorial to learn more about GNNs. In the last step, they create a visualization of the network training, using the following code: ...
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1answer
187 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 ...