Deep Ritz revisited J Müller, M Zeinhofer DeepDiffEq workshop at ICLR 2020, 2020 | 17 | 2020 |

Error estimates for the deep Ritz method with boundary penalty J Müller, M Zeinhofer Mathematical and Scientific Machine Learning, 215-230, 2022 | 12* | 2022 |

On the space-time expressivity of ResNets J Müller DeepDiffEq workshop at ICLR 2020, 2020 | 6* | 2020 |

Notes on Exact Boundary Values in Residual Minimisation M Zeinhofer Proceedings of Machine Learning Research vol 145, 1-13, 2022 | 5* | 2022 |

Uniform Convergence Guarantees for the Deep Ritz Method for Nonlinear Problems P Dondl, J Müller, M Zeinhofer Advances in Continuous and Discrete Models, 2022 | 3 | 2022 |

Universal flow approximation with deep residual networks J Müller University of Freiburg, 2019 | 3 | 2019 |

The Geometry of Memoryless Stochastic Policy Optimization in Infinite-Horizon POMDPs G Montúfar, J Müller 10th International Conference of Learning Representations (ICLR 2022), 2022 | 2* | 2022 |

Invariance properties of the natural gradient in overparametrised systems J van Oostrum, J Müller, N Ay Information Geometry, 1-17, 2022 | | 2022 |

Solving infinite-horizon POMDPs with memoryless stochastic policies in state-action space J Müller, G Montúfar 5th Multi-disciplinary Conference on Reinforcement Learning and Decision …, 2022 | | 2022 |

Parameter estimation and consistency for discrete determinantal point processes J Müller University of Warwick, 2018 | | 2018 |