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"Machine Learning for Conservative-to-Primitive in Relativistic Hydrodynamics."

Tobias Dieselhorst et al. (2021)

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DOI: 10.3390/SYM13112157

access: open

type: Journal Article

metadata version: 2021-12-25

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  dblp key:
  - journals/symmetry/DieselhorstCBR21
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  - https://dblp.org/rec/journals/symmetry/DieselhorstCBR21
Tobias Dieselhorst, William Cook, Sebastiano Bernuzzi, David Radice:
Machine Learning for Conservative-to-Primitive in Relativistic Hydrodynamics. Symmetry 13(11): 2157 (2021)

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