Questions tagged [graphs]

Use for questions related to graph coloring and graph coloring games.

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58 views

What is Precision@K for link prediction in graph embedding meaning?

I am trying to re-implement the SDNE algorithm for graph embedding by PyTorch. I get stuck at some issues about evaluation metric Precision@K. precision@k is a metric which gives equal weight to the ...
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36 views

How do I interpret the following parameters as a network

I have a background in OR and I am new to AI. I know the basics and I currently try to understand the article "Learning Combinatorial Optimization Algorithms over Graphs". So far I ...
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26 views

How to learn how to select a subgraph via reinforcement learning?

I have the following problem. I am given a graph with a lot (>30000) nodes. Nodes are associated with a low (<10)-dimensional feature vector, and edges are associated with a low (<10)-...
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43 views

Applications of polar decomposition in Machine Learning

Assume there exists a new and very efficient algorithm for calculating the polar decomposition of a matrix $A=UP$, where $U$ is a unitary matrix and $P$ is a positive-semidefinite Hermitian matrix. ...
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40 views

If artificial neural networks are a special case of computation graphs, so maybe let's optimize computational graphs rather than neural networks?

Existing ANNs are so good for solving complicated tasks on a different domain of data. But creating a neural network is always a hassle and its success mostly relies on an engineer's intuition and ...
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1answer
69 views

How can I learn a graph given nodes with features in a supervised fashion?

I have a dataset and want to be able to construct a graph from it in a supervised fashion. Let's assume I have a dataset with N nodes, each node has e.g. 10 features. Out of these N nodes, I want to ...
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35 views

Model for supervised sequence classification task

The Problem I am currently working on a sequence classification problem I try to solve with machine learning. The target variable is the current state of a system. This target variable is following a ...
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0answers
21 views

How to update edge features in a graph using a loss function?

Given a directed, edge attributed graph G, where the edge attribute is a probability value, and a particular node N (with binary features f1 and f2) in G, the algorithm that I want to implement is as ...
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44 views

Suitable deep learning algorithms for spatial / geometric data

I have a task of classifying spatial data from a geographic information system. More precisely, I need a way to filter out unnecessary line segments from the CAD system before loading into the GIS (...
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0answers
91 views

Can the degree and minimum remaining values heuristics be used in conjunction?

I am currently studying constraint satisfaction problems and have come across two heuristics for variable selection. The minimum remaining values(MRV) heuristic and the degree heuristic. The MRV ...
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1answer
53 views

How to solve the problem of variable-sized AST as input for a (convolutional) neural network model?

In my work I have a given source code for a module. From this module I generate an AST, whose size is dependent on the size of the module (e.g. more source code -> bigger AST). I want to train a ...
2
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1answer
37 views

What is the difference between graph semi-supervised learning and normal semi-supervised learning?

Whenever I look for papers involving semi-supervised learning, I always find some that talk about graph semi-supervised learning (e.g. A Unified Framework for Data Poisoning Attack to Graph-based Semi-...
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13 views

Improving graph decoder network

I have been using a network to generate graphs. The architecture that I have been using is the following: In this figure, $D_1$ is the signal generator and $D_2$ is the graph topology generator, ...
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2answers
102 views

Is there an open-source implementation for graph convolution networks for weighted graphs?

Currently, I'm using a Python library, StellarGraph, to implement GCN. And I now have a situation where I have graphs with weighted edges. Unfortunately, StellarGraph doesn't support those graphs I'm ...
4
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1answer
56 views

What are the exact meaning of “lower-order structure” and “higher-order structure” in this paper?

I recently read a paper on community detection in networks. In the paper EdMot: An Edge Enhancement Approach for Motif-aware Community Detection, the authors consider the "lower-order structure" of ...
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78 views

How to build naive bayes graph from data

For an university assignment I have to use the HuginLite software to do some probabilistic inferences with different algorithms. One of these algorithms is Naive Bayes but its graph is not built ...
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1answer
93 views

Does GraphSage use hard attention?

I was reading the recent paper Graph Representation Learning via Hard and Channel-Wise Attention Networks, where the authors claim that there is no hard attention operator for graph data. From my ...
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29 views

What are the advantages of time-varying graph CNNs compared to fixed graph?

As I wrote in the title, what are the advantages of time-varying graph CNNs compared to fixed graph? For example, in CORA, which is a graph of citation relations of papers frequently used in graph CNN,...
2
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1answer
113 views

Is there a neural network method for time-varying directed graphs?

I want to study NN for time-varying directed graphs. However, as this field has developed relatively recently, it is difficult to find new ways. So the question is, is there any NN that can handle ...
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0answers
24 views

Random graph as input in geometric deep learning on time-varying graph

I want to create a framework that allows GDL to be applied to time-varying graphs. I came up with the Erdos-renyi model as an example of a time-varying graphs. GDL for graphs takes node information ...
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2answers
101 views

What are the differences between network analysis and geometric deep learning on graphs?

Both of them deal with data of graph structure like a network community. Is there a big difference there?
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38 views

What are the benefits of using the state information that maintains the graph structure?

When you applying a graph structured data to the graph convolution network, what are the benefits of using the state information that maintains the graph structure?
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2answers
158 views

Are there neural networks that accept graphs or trees as inputs?

As far I know, the RNN accepts a sequence as input and can produce as a sequence as output. Are there neural networks that accept graphs or trees as inputs, so that to represent the relationships ...
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27 views

Write Constraint Satisfaction Formulation for problem

Given $F_1,F_2,..,F_n$ as set of final exams of subjects taken by students $S_1,..,S_k$ in h slots such that no student takes two exams in a single slot.Here the objective is to maximize the number of ...
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2answers
58 views

What is the proof that the branch and bound algorithm always finds optimal path in a graph?

I've been studying Branch and Bound's graph algorithm and I hear it always finds the optimal path because it uses previously found solutions to find others However, I haven't been able to find a ...
3
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1answer
266 views

Using graph searching to solve peg solitaire?

Problem: I've been reading research papers on how to solve a peg solitaire using graph searching, but all the papers kind of assume you know how to do the reduction(polynomial time conversion) from ...
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3answers
5k views

What is non-Euclidean data?

What is non-Euclidean data? Where does this type of data arises? Apparently, graphs and manifolds are non-Euclidean data. Why exactly is that the case? What is the difference between non-Euclidean and ...
4
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1answer
299 views

What is a graph neural network?

What is a graph neural network (GNN)? How is a GNN different from a NN? How exactly is a GNN related to graphs? What are the components of a GNN? What are the inputs and outputs of GNNs? How can ...
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2answers
2k views

What is geometric deep learning?

What is geometric deep learning (GDL)? How is it different from deep learning? Why do we need GDL? What are some applications of GDL?
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69 views

How to create meaningful multiple object detection evaluation comparison graph?

I have got multi-class object detector. One model accuracy evaluation of detection consists of: mAP, FP, FN, TP for each class divided to two graphs and looks like this (I've used this repo for ...
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2answers
871 views

What benefits can be got by applying Graph Convolutional Neural Network instead of ordinary CNN?

What benefits can we got by applying Graph Convolutional Neural Network instead of ordinary CNN? I mean if we can solve a problem by CNN, what is the reason should we convert to Graph Convolutional ...
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0answers
32 views

How to visualize/interpret text prediction model results?

I am using LSTM model to predict the next xml markup from an input seed. I have trained my model on 1500 xml files. Each xml file is generated randomly. I am wondering if there is a way to visualize ...
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2answers
404 views

Neural network for data visualization

At my work we're currently doing some research into data visualisation for highly inter connected data, basically graphs. We've been implementing all sorts of different layouts and trying to see ...
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2answers
1k views

Machine learning with graph as input and output

In my application, I have inputs and outputs that could be represented as graphs. I have a number of acceptable pairs of input and output graphs. I want to use these to train a model. I am looking ...