Software Open Access
Creutzburg, Sascha;
Rustamov, Jeyhun;
Bornschein, Jens;
Ganeva, Marina;
Gerlach, Alexander;
Häusler, Stefan;
Helm, Bernd;
Hinderhofer, Alexander;
Juzak, Robert;
Koutsioumpas, Alexandros;
Munteanu, Valentin;
Pandit, Vedhas Sadanand;
Schreiber, Frank;
Mothes, Nico;
Kelling, Jeffrey
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"description": "<p>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.</p>",
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| All versions | This version | |
|---|---|---|
| Views | 93 | 93 |
| Downloads | 4 | 4 |
| Data volume | 102.4 MB | 102.4 MB |
| Unique views | 89 | 89 |
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