https://github.com/laurencee9/structural_pertubation_detection
Official torch geometric code for the paper Detecting structural perturbations from time series with deep learning
https://github.com/laurencee9/structural_pertubation_detection
anomaly-detection complexnetworks deep-learning graph graphneuralnetwork
Last synced: 9 months ago
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Official torch geometric code for the paper Detecting structural perturbations from time series with deep learning
- Host: GitHub
- URL: https://github.com/laurencee9/structural_pertubation_detection
- Owner: laurencee9
- Created: 2021-03-05T02:13:26.000Z (about 5 years ago)
- Default Branch: main
- Last Pushed: 2021-03-05T02:19:26.000Z (about 5 years ago)
- Last Synced: 2025-03-03T11:44:16.536Z (over 1 year ago)
- Topics: anomaly-detection, complexnetworks, deep-learning, graph, graphneuralnetwork
- Language: Jupyter Notebook
- Homepage: https://arxiv.org/pdf/2006.05232.pdf
- Size: 279 KB
- Stars: 4
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Detecting structural perturbations from time series with deep learning
Official torch geometric code for the paper *Detecting structural perturbations from time series with deep learning*
- [Paper](https://arxiv.org/pdf/2006.05232.pdf)
- [Notebooks](./notebooks)
## Install
You can install the package using:
```
python setup.py install
```
Make sure your python env fulfills all the requirements from `requirements.txt`.
Tested with packages
```
python==3.8
torch==1.7.1
torch_geometric==1.6.3
networkx==2.5
```
## Examples
Check the [notebooks](./notebooks) for complete examples of predictions.
## Contributors
- [Edward Laurence](https://github.com/laurencee9)
- [Charles Murphy](https://github.com/charlesmurphy1)
- [Guillaume St-Onge](https://github.com/gstonge)
- [Xavier Roy-Pomerleau](https://github.com/xavier-rp)
- [Vincent Thibeault](https://github.com/VinceThi)