improved overview references

overview.md

@@ -89,13 +89,13 @@ a neural network that supports the repeated solves. Based on the
 domain-specific specialization of this network, such a hybrid
 could vastly outperform traditional, generic solvers. And despite
 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
 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 
 big step forward, DL methods offer a very powerful tool to close the
-remaining gap towards reality.
+remaining gap towards reality {cite}`akkaya2019solving`.
 
 ## Categorization
 

references.bib

@@ -918,4 +918,21 @@
   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}
+}
+