Commit f96104a1 authored by Manuel Marschall's avatar Manuel Marschall
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# datainformed-prior
# License
copyright Manuel Marschall (PTB) 2022
This software is licensed under the BSD-like license:
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in
the documentation and/or other materials provided with the distribution.
This software was developed at Physikalisch-Technische Bundesanstalt
(PTB). The software is made available "as is" free of cost. PTB assumes
no responsibility whatsoever for its use by other parties, and makes no
guarantees, expressed or implied, about its quality, reliability, safety,
suitability or any other characteristic. In no event will PTB be liable
for any direct, indirect or consequential damage arising in connection
# Generative models and Bayesian inversion using Laplace approximation
This project contains the implementation of the manuscript
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 ``.
Alternativle, for problems regarding the code, its functionality oder bug-reports, please create an issue.
# Code base
To run the library, one needs a python 3.7 installation with the python packages given in the `requirements.txt`
We propose to use an anaconda environment. In particular, clone the repository and use the following for installation:
conda create -n GenerativeBayes python==3.7
pip install -r requirements.txt
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