Software Open Access
VIPR (Versatile Inverse Problem Software Framework) unified demonstrator
Creutzburg, Sascha;
Rustamov, Jeyhun;
Bornschein, Jens;
Ganeva, Marina;
Gerlach, Alexander;
Häusler, Stefan;
Helm, Bernd;
Hinderhofer, Alexander;
Juzak, Robert;
Koutsioumpas, Alexandros;
Munteanu, Valentin;
Pandit, Vedhas;
Schreiber, Frank;
Mothes, Nico;
Kelling, Jeffrey
VIPR (Versatile Inverse Problem Software Framework) is a plugin-based framework for reproducible machine-learning-driven solutions to scientific inverse problems. It addresses ill-posed reconstruction tasks caused by loss of phase information during measurement, where direct inversion is not possible. It implements a modular architecture with domain-specific plugins to produce configurable machine learning workflows, including both deterministic and probabilistic models. Workflows are defined via declarative YAML configurations and can be executed through a command-line interface or a containerized web application. For a given experimental dataset, VIPR produces standardized analysis artifacts, including visualizations and statistical summaries.
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vipr_demonstrator.tgz
md5:0de122b993300b5e22476e34c7a1370b |
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- Publication date:
- April 29, 2026
- DOI:
-
- Keyword(s):
- Ill-posed Inverse Problems Reflectometry Machine Learning
- Related identifiers:
- Identical to:
https://www.hzdr.de/publications/Publ-43563 - Supplementary material:
10.14278/rodare.4504, 10.57967/hf/8498 - Communities:
- License (for files):
- GNU Lesser General Public License v3.0 or later