Information Field Theory for Two Applications in Astroparticle Physics
Information field theory (IFT) provides a powerful framework for reconstructing continuous fields from noisy and sparse data. Based on Bayesian statistics, IFT allows for the approximation of posterior distributions over field-like parameter spaces in high-dimensional problems. In this contribution,...
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| Main Authors: | Martin Erdmann, Frederik Krieger, Alex Reuzki, Josina Schulte, Michael Smolka, Maximilian Straub |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Particles |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2571-712X/8/2/39 |
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