| Constraint-aware neural networks for Riemann problems J Magiera, D Ray, JS Hesthaven, C Rohde Journal of Computational Physics 409, 109345, 2020 | 62 | 2020 |
| A multiple-time-step technique for coupled free flow and porous medium systems I Rybak, J Magiera Journal of Computational Physics 272, 327-342, 2014 | 55 | 2014 |
| Multirate time integration for coupled saturated/unsaturated porous medium and free flow systems I Rybak, J Magiera, R Helmig, C Rohde Computational Geosciences 19 (2), 299-309, 2015 | 52 | 2015 |
| A hyperbolic–elliptic model problem for coupled surface–subsurface flow J Magiera, C Rohde, I Rybak Transport in Porous Media 114 (2), 425-455, 2016 | 9 | 2016 |
| A molecular–continuum multiscale model for inviscid liquid–vapor flow with sharp interfaces J Magiera, C Rohde Journal of Computational Physics 469, 111551, 2022 | 5 | 2022 |
| A finite-volume tracking scheme for two-phase compressible flow C Chalons, J Magiera, C Rohde, M Wiebe Theory, Numerics and Applications of Hyperbolic Problems I: Aachen, Germany …, 2018 | 4 | 2018 |
| A particle-based multiscale solver for compressible liquid–vapor flow J Magiera, C Rohde Theory, Numerics and Applications of Hyperbolic Problems II: Aachen, Germany …, 2018 | 4 | 2018 |
| A molecular-continuum multiscale solver for liquid-vapor flow: modeling and numerical simulation J Magiera | 2 | 2021 |
| Analysis and Numerics of Sharp and Diffuse Interface Models for Droplet Dynamics J Magiera, C Rohde Droplet Dynamics Under Extreme Ambient Conditions, 67-86, 2022 | 1 | 2022 |
| An interface preserving moving mesh in multiple space dimensions M Alkämper, J Magiera, C Rohde ACM Transactions on Mathematical Software, 2021 | 1 | 2021 |
| Decoupled schemes for free flow and porous medium systems I Rybak, J Magiera Domain Decomposition Methods in Science and Engineering XXII, 613-621, 2016 | 1 | 2016 |
| A Multiscale Method for Two-Component, Two-Phase Flow with a Neural Network Surrogate J Magiera, C Rohde arXiv preprint arXiv:2309.00876, 2023 | | 2023 |
| On the use of artificial neural networks when solving conservation laws O Bruno, N Discacciati, JS Hesthaven, DV Leibovici, J Magiera, D Ray, ... Málaga, 2022 | | 2022 |
| Deep Ray, Jan S Hesthaven, and Christian Rohde. Constraint-aware neural networks for riemann problems J Magiera arXiv preprint arXiv:1904.12794, 2019 | | 2019 |
Christian RohdeUniversität StuttgartΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα mathematik.uni-stuttgart.de
