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: about 5 hours 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 6 years ago)
• Default Branch: master
• Last Pushed: 2023-02-10T23:09:43.000Z (almost 2 years ago)
• Last Synced: 2024-04-16T02:14:54.366Z (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: 5
• Forks: 4
• Open Issues: 5
• 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 .

```