"A machine learning pipeline for autonomous numerical analytic continuation ..."

Andreas Windisch, Thomas Gallien, Christopher Schwarzlmüller (2021)

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DOI: —

access: open

type: Informal or Other Publication

metadata version: 2022-01-05

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  - electronic edition @ arxiv.org (open access)
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  dblp key:
  - journals/corr/abs-2112-13011
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  - https://dblp.org/rec/journals/corr/abs-2112-13011
Andreas Windisch, Thomas Gallien, Christopher Schwarzlmüller:
A machine learning pipeline for autonomous numerical analytic continuation of Dyson-Schwinger equations. CoRR abs/2112.13011 (2021)

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