Commit 86b49a9a authored by Manuel Marschall's avatar Manuel Marschall
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adjusted readme

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# Generative models and Bayesian inversion using Laplace approximation
This project contains the implementation of the manuscript
This project contains the implementation for the examples in the [manuscript](http://arxiv.org/abs/2203.07755)
```
M. Marschall, G. Wübbeler, F. Schmähling and C. Elster "Generative models and Bayesian inversion using Laplace approximation".
```
# Contact and troubleshooting
For direct contact, please write a quick mail to `manuel.marschall@ptb.de`.
Alternativle, for problems regarding the code, its functionality oder bug-reports, please create an issue.
For direct contact, please write a quick mail to `manuel.marschall@ptb.de` or create an issue.
# Code base
......@@ -44,4 +43,14 @@ We propose to use an anaconda environment. In particular, clone the repository a
```
conda create -n GenerativeBayes python==3.7
pip install -r requirements.txt
```
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```
# Run the code
Simply call
```
python datainformed_prior/experiments_runner.py -n 100
```
Depending on your system, this might take a long time. With computations carried out on a Nvidia Tesla V100, the results are available in approximately 24h. Therefore, reduce the number of runs to `-n 3` for a smaller statistic. The final results are given in `paper_plots/`
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