1. Abgrall, R.: Residual distribution schemes: current status and future trends. Comput. Fluids 35(7), 641–669 (2006). https://doi.org/10.1016/j.compfluid.2005.01.007
2. Abgrall, R., Bacigaluppi, P., Tokareva, S.: High-order residual distribution scheme for the time-dependent Euler equations of fluid dynamics. Comput. Math. Appl. 78(2), 274–297 (2019). https://doi.org/10.1016/j.camwa.2018.05.009
3. Bacigaluppi, P., Abgrall, R., Tokareva, S.: “A posteriori” limited high order and robust residual distribution schemes for transient simulations of fluid flows in gas dynamics. arXiv:1902.07773 (2019)
4. Beck, A., Zeifang, J., Schwarz, A., Flad, D.: A neural network based shock detection and localization approach for discontinuous Galerkin methods (2020). https://doi.org/10.13140/RG.2.2.20237.90085
5. Bergstra, J., Yamins, D., Cox, D.: Making a science of model search: hyperparameter optimization in hundreds of dimensions for vision architectures. In: Dasgupta, S., McAllester, D. (eds.) Proceedings of the 30th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol. 28, pp. 115–123. PMLR, Atlanta (2013). http://proceedings.mlr.press/v28/bergstra13.html