What do language representations really represent? J Bjerva, R Östling, MH Veiga, J Tiedemann, I Augenstein Computational Linguistics 45 (2), 381-389, 2019 | 39 | 2019 |

A cross-platform collection of social network profiles M Han Veiga, C Eickhoff Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016 | 16 | 2016 |

Privacy leakage through innocent content sharing in online social networks MH Veiga, C Eickhoff arXiv preprint arXiv:1607.02714, 2016 | 14 | 2016 |

Dec and Ader: similarities, differences and a unified framework M Han Veiga, P Öffner, D Torlo Journal of Scientific Computing 87 (1), 1-35, 2021 | 8 | 2021 |

Machine learning applied to simulations of collisions between rotating, differentiated planets ML Timpe, M Han Veiga, M Knabenhans, J Stadel, S Marelli Computational astrophysics and cosmology 7 (1), 1-38, 2020 | 7 | 2020 |

Towards a general stabilisation method for conservation laws using a multilayer perceptron neural network: 1d scalar and system of equations MH Veiga, R Abgrall ECCM-ECFD 2018 6th European Conference on Computational Mechanics (Solids …, 2018 | 7 | 2018 |

An arbitrary high-order Spectral Difference method for the induction equation MH Veiga, DA Velasco-Romero, Q Wenger, R Teyssier Journal of Computational Physics 438, 110327, 2021 | 6 | 2021 |

Capturing near-equilibrium solutions: a comparison between high-order discontinuous Galerkin methods and well-balanced schemes MH Veiga, DAR Velasco, R Abgrall, R Teyssier arXiv preprint arXiv:1803.05919, 2018 | 6 | 2018 |

Planet–disc interactions with discontinuous Galerkin methods using GPUs DA Velasco Romero, M Han Veiga, R Teyssier, FS Masset Monthly Notices of the Royal Astronomical Society 478 (2), 1855-1865, 2018 | 4 | 2018 |

Neural network-based limiter with transfer learning R Abgrall, M Han Veiga Communications on Applied Mathematics and Computation, 1-41, 2020 | 3 | 2020 |

Neural network based limiter with transfer learning MH Veiga, R Abgrall arXiv preprint arXiv:1912.09274, 2019 | 2 | 2019 |

Towards a general stabilisation method for conservation laws using a multilayer Perceptron neural network: 1D scalar and system of equations M Han Veiga, R Abgrall HAL 2018, 2018 | 1 | 2018 |

Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning MH Veiga, X Meng, OY Gnedin, NY Gnedin, X Huan arXiv preprint arXiv:2107.09082, 2021 | | 2021 |

Comparison of machine learning techniques for emulating collisions in planet formation M Timpe, M Han Veiga, M Knabenhans AAS/Division for Extreme Solar Systems Abstracts 51, 318.14, 2019 | | 2019 |

Exploring numerical schemes for conservation laws MH Veiga | | 2019 |

High Order Structure Preserving Numerical Schemes for Astrophysical Flows M Han Veiga University of Zurich, 2019 | | 2019 |

Emulating Collisions for N-body M Timpe, M Knabenhans, MH Veiga, J Stadel, S Marelli | | |

Towards a general limiter for systems of conservation laws: 1D scalar and system of equations MH Veiga, R Abgrall, W Zurich | | |