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improved overview references

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2021-08-21 20:45:58 +02:00
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overview.md
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@@ -89,13 +89,13 @@ a neural network that supports the repeated solves. Based on the
domain-specific specialization of this network, such a hybrid domain-specific specialization of this network, such a hybrid
could vastly outperform traditional, generic solvers. And despite could vastly outperform traditional, generic solvers. And despite
the many open questions, first publications have demonstrated the many open questions, first publications have demonstrated
that this goal is not overly far away. that this goal is not overly far away {cite}`um2020sol,kochkov2021`.
Another way to look at it is that all mathematical models of our nature Another way to look at it is that all mathematical models of our nature
are idealized approximations and contain errors. A lot of effort has been are idealized approximations and contain errors. A lot of effort has been
made to obtain very good model equations, but in order to make the next made to obtain very good model equations, but in order to make the next
big step forward, DL methods offer a very powerful tool to close the big step forward, DL methods offer a very powerful tool to close the
remaining gap towards reality. remaining gap towards reality {cite}`akkaya2019solving`.
## Categorization ## Categorization

17
references.bib
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@@ -918,4 +918,21 @@
year={2015} year={2015}
} }
@article{kochkov2021,
title={Machine learning--accelerated computational fluid dynamics},
author={Kochkov, Dmitrii and Smith, Jamie A and Alieva, Ayya and Wang, Qing and Brenner, Michael P and Hoyer, Stephan},
journal={Proceedings of the National Academy of Sciences},
volume={118},
number={21},
year={2021},
publisher={National Acad Sciences}
}
@article{akkaya2019solving,
title={Solving rubik's cube with a robot hand},
author={Akkaya, Ilge and Andrychowicz, Marcin and Chociej, Maciek and Litwin, Mateusz and McGrew, Bob and others},
journal={arXiv:1910.07113},
year={2019}
}