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Removal of bremsstrahlung background from SAXS signals with deep neural networks: sourcecode

Starke, Sebastian; Smid, Michal

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{
  "abstract": "<p>This repository contains the sourcecode used to train neural networks for the removal of bremsstrahlung background from SAXS data. Also, it offers a script to apply trained models to new noisy data.</p>", 
  "author": [
    {
      "family": "Starke, Sebastian"
    }, 
    {
      "family": "Smid, Michal"
    }
  ], 
  "publisher": "Rodare", 
  "id": "4976", 
  "issued": {
    "date-parts": [
      [
        2026, 
        8, 
        25
      ]
    ]
  }, 
  "DOI": "10.14278/rodare.4976", 
  "type": "article", 
  "version": "v0.1.0", 
  "title": "Removal of bremsstrahlung background from SAXS signals with deep neural networks: sourcecode"
}
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Publication date:
August 25, 2026
DOI:
10.14278/rodare.4976

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10.14278/rodare.4976

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Keyword(s):
SAXS XFEL equivariant neural networks noise removal
Related identifiers:
Compiles:
https://www.hzdr.de/publications/Publ-37977, 10.14278/rodare.4956
Has part:
https://github.com/Helmholtz-AI-Matter/bremsstrahlung_denoising/tree/v0.1.0
Identical to:
https://www.hzdr.de/publications/Publ-43791
Communities:
License (for files):
MIT License

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Version v0.1.0 10.14278/rodare.4976 Aug 25, 2026
Cite all versions? You can cite all versions by using the DOI 10.14278/rodare.4975. This DOI represents all versions, and will always resolve to the latest one. Read more.

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