https://github.com/networks-learning/disease-control
Code and data for "Stochastic Optimal Control of Epidemic Processes in Networks", ML4H at NeurIPS 2018
https://github.com/networks-learning/disease-control
control disease-control machine-learning networks point-processes
Last synced: 6 months ago
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Code and data for "Stochastic Optimal Control of Epidemic Processes in Networks", ML4H at NeurIPS 2018
- Host: GitHub
- URL: https://github.com/networks-learning/disease-control
- Owner: Networks-Learning
- Created: 2018-11-26T17:51:54.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2023-02-10T23:09:43.000Z (over 2 years ago)
- Last Synced: 2025-03-30T01:51:47.569Z (7 months ago)
- Topics: control, disease-control, machine-learning, networks, point-processes
- Language: Jupyter Notebook
- Homepage: https://arxiv.org/abs/1810.13043
- Size: 43.4 MB
- Stars: 12
- Watchers: 4
- Forks: 4
- Open Issues: 5
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Metadata Files:
- Readme: README.md
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README
# disease-control
This is the code for the simulation of the project on disease control with SDEs with jumps.
The following describes the different files and how they interact.
## Installation
To run the experiment notebooks, first install the internal library using:
```
python setup.py install -e .
```