| Learning macroscopic internal variables and history dependence from microscopic models B Liu, E Ocegueda, M Trautner, AM Stuart, K Bhattacharya Journal of the Mechanics and Physics of Solids 178, 105329, 2023 | 13 | 2023 |
| Informative neural ensemble Kalman learning M Trautner, G Margolis, S Ravela arXiv preprint arXiv:2008.09915, 2020 | 9 | 2020 |
| Learning Markovian homogenized models in viscoelasticity K Bhattacharya, B Liu, A Stuart, M Trautner Multiscale Modeling & Simulation 21 (2), 641-679, 2023 | 8 | 2023 |
| Neural integration of continuous dynamics M Trautner, S Ravela arXiv preprint arXiv:1911.10309, 2019 | 7 | 2019 |
| An operator learning perspective on parameter-to-observable maps DZ Huang, NH Nelsen, M Trautner arXiv preprint arXiv:2402.06031, 2024 | 3 | 2024 |
| Learn like the pro: Norms from theory to size neural computation M Trautner, Z Li, S Ravela arXiv preprint arXiv:2106.11409, 2021 | 3 | 2021 |
| Learning homogenization for elliptic operators K Bhattacharya, N Kovachki, A Rajan, AM Stuart, M Trautner arXiv preprint arXiv:2306.12006, 2023 | 2 | 2023 |
| Informative ensemble Kalman learning for neural structure M Trautner, G Margolis, S Ravela Dynamic Data Driven Applications Systems: Third International Conference …, 2020 | 1 | 2020 |
