Deep Learning Based Cloud Cover Parameterization for ICON A Grundner, T Beucler, F Iglesias-Suarez, P Gentine, MA Giorgetta, ... Journal of Advances in Modeling Earth Systems (JAMES), 2022 | 17 | 2022 |
Data-driven equation discovery of a cloud cover parameterization A Grundner, T Beucler, P Gentine, V Eyring arXiv preprint arXiv:2304.08063, 2023 | 8 | 2023 |
Machine Learning for Hidden Physics and Partial Differential Equations. 2018 A Ratnani, K Harsha, A Grundner, K Wang URL: https://github. com/ratnania/mlhiphy, 0 | 2 | |
Data‐driven equation discovery of a cloud cover parameterization A Grundner, T Beucler, P Gentine, V Eyring Journal of Advances in Modeling Earth Systems 16 (3), e2023MS003763, 2024 | 1 | 2024 |
Systematically generating hierarchies of machine-learning models, from equation discovery to deep neural networks (core science keynote) TG Beucler, A Grundner, R Lagerquist, S Shamekh 103rd AMS Annual Meeting, 2023 | 1 | 2023 |
Machine Learning-Based Causally Informed Atmospheric Parametrizations for Climate Models V Eyring, A Grundner, F Iglesias-Suarez, T Beucler, P Gentine, GA Marco, ... AGU Fall Meeting Abstracts 2022, NG16A-03, 2022 | 1 | 2022 |
Data-Driven Cloud Cover Parameterizations for the ICON Earth System Model Using Deep Learning and Symbolic Regression A Grundner Staats-und Universitätsbibliothek Bremen, 2023 | | 2023 |
ML developments for ICON and Evaluation with ESMValTool M Schwabe, P Bonnet, A Grundner, M Schlund, V Eyring | | 2023 |
Data-Driven Cloud Cover Parameterizations A Grundner, T Beucler, P Gentine, MA Giorgetta, F Iglesias-Suarez, ... EGU General Assembly Conference Abstracts, EGU-6306, 2023 | | 2023 |
Machine learning-based parametrizations for the ICON model F Iglesias-Suarez, A Grundner, G Behrens, T Beucler, P Gentine, G Marco, ... AGU Fall Meeting Abstracts 2021, A14C-04, 2021 | | 2021 |
Parameter Estimation with Gaussian Processes K Harsha, A Grundner, K Wang | | 2018 |
TUM-DI-LAB Report K Harsha, A Grundner, K Wang | | 2018 |
HOL Foundations A Grundner | | 2018 |