| Can deep learning beat numerical weather prediction? MG Schultz, C Betancourt, B Gong, F Kleinert, M Langguth, LH Leufen, ... Philosophical Transactions of the Royal Society A 379 (20200097), 2021 | 303 | 2021 |
| Global, high-resolution mapping of tropospheric ozone–explainable machine learning and impact of uncertainties C Betancourt, TT Stomberg, AK Edrich, A Patnala, MG Schultz, R Roscher, ... Geoscientific model development 15 (11), 4331-4354, 2022 | 21 | 2022 |
| AQ-Bench: a benchmark dataset for machine learning on global air quality metrics C Betancourt, T Stomberg, S Stadtler, R Roscher, MG Schultz Earth System Science Data Discussions 2021, 1-26, 2021 | 16 | 2021 |
| Explainable machine learning reveals capabilities, redundancy, and limitations of a geospatial air quality benchmark dataset S Stadtler, C Betancourt, R Roscher Machine learning and knowledge extraction 4 (1), 150-171, 2022 | 13 | 2022 |
| Can deep learning beat numerical weather prediction?, Philos MG Schultz, C Betancourt, B Gong, F Kleinert, M Langguth, LH Leufen, ... Roy. Soc. A 379 (20200097), 10.1098, 2021 | 13 | 2021 |
| Can deep learning beat numerical weather prediction?, Philos. T. Roy. Soc. A, 379, 20200097 MG Schultz, C Betancourt, B Gong, F Kleinert, M Langguth, LH Leufen, ... | 8 | 2021 |
| AQ-Bench: a benchmark dataset for machine learning on global air quality metrics, Earth Syst. Sci. Data, 13, 3013–3033 C Betancourt, T Stomberg, R Roscher, MG Schultz, S Stadtler | 6 | 2021 |
| Graph Machine Learning for Improved Imputation of Missing Tropospheric Ozone Data C Betancourt, CWY Li, F Kleinert, MG Schultz Environmental Science & Technology 57 (46), 18246-18258, 2023 | 3 | 2023 |
| TOAR Data Infrastructure S Schröder, MG Schultz, N Selke, J Sun, J Ahring, A Mozaffari, ... Version v1. 0, FZ-Juelich B2SHARE [data set] 10, 2021 | 3 | 2021 |
| Context aware benchmarking and tuning of a TByte-scale air quality database and web service C Betancourt, B Hagemeier, S Schröder, MG Schultz Earth science informatics 14 (3), 1597-1607, 2021 | 2 | 2021 |
| Firewood residential heating–local versus remote influence on the aerosol burden C Betancourt, C Küppers, T Piansawan, U Sager, AB Hoyer, H Kaminski, ... Atmospheric chemistry and physics 21 (8), 5953-5964, 2021 | 1 | 2021 |
| Global fine resolution mapping of ozone metrics through explainable machine learning C Betancourt, S Stadtler, T Stomberg, AK Edrich, A Patnala, R Roscher, ... EGU General Assembly, 2021 | 1 | 2021 |
| Lagrangian particle dispersion modeling of stable carbon isotope ratios to track the chemical aging of biomass burning aerosol C Betancourt, S Crewell, A Kiendler-Scharr Jülich Supercomputing Center, 2019 | 1 | 2019 |
| Mapping and Interpolation of Tropospheric Ozone Data with Machine Learning Methods C Betancourt Universitäts-und Landesbibliothek Bonn, 2023 | | 2023 |
| Firewood residential heating–local versus regional influence on the aerosol burden C Betancourt, C Küppers, U Sager, AB Hoyer, H Kaminski, G Rapp, ... European Aerosol Conference 2020, 2020 | | 2020 |
| Performance analysis and optimization of a TByte-scale atmospheric observation database C Betancourt, S Schröder, B Hagemeier, M Schultz EGU2020: Sharing Geoscience Online, 2020 | | 2020 |
