| Rainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory network M Gauch, F Kratzert, D Klotz, G Nearing, J Lin, S Hochreiter Hydrology and Earth System Sciences 25 (4), 2045-2062, 2021 | 140 | 2021 |
| The proper care and feeding of CAMELS: How limited training data affects streamflow prediction M Gauch, J Mai, J Lin Environmental Modelling & Software 135, 104926, 2021 | 113 | 2021 |
| Deep learning rainfall-runoff predictions of extreme events J Frame, F Kratzert, D Klotz, M Gauch, G Shelev, O Gilon, LM Qualls, ... Copernicus GmbH, 2021 | 105 | 2021 |
| Uncertainty estimation with deep learning for rainfall–runoff modeling D Klotz, F Kratzert, M Gauch, A Keefe Sampson, J Brandstetter, ... Hydrology and Earth System Sciences 26 (6), 1673-1693, 2022 | 90 | 2022 |
| Hydrological concept formation inside long short-term memory (LSTM) networks T Lees, S Reece, F Kratzert, D Klotz, M Gauch, J De Bruijn, R Kumar Sahu, ... Hydrology and Earth System Sciences Discussions 2021, 1-37, 2021 | 73 | 2021 |
| Caravan - A global community dataset for large-sample hydrology F Kratzert, G Nearing, N Addor, T Erickson, M Gauch, O Gilon, ... EarthArXiv, 2022 | 43 | 2022 |
| The great lakes runoff intercomparison project phase 4: the great lakes (GRIP-GL) J Mai, H Shen, BA Tolson, É Gaborit, R Arsenault, JR Craig, V Fortin, ... Hydrology and Earth System Sciences 26 (13), 3537-3572, 2022 | 42 | 2022 |
| NeuralHydrology—A Python library for Deep Learning research in hydrology F Kratzert, M Gauch, G Nearing, D Klotz Journal of Open Source Software 7 (71), 4050, 2022 | 37 | 2022 |
| Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks GS Nearing, D Klotz, JM Frame, M Gauch, O Gilon, F Kratzert, ... Hydrology and Earth System Sciences 26 (21), 5493-5513, 2022 | 29 | 2022 |
| Great Lakes runoff intercomparison project phase 3: Lake Erie (GRIP-E) J Mai, BA Tolson, H Shen, É Gaborit, V Fortin, N Gasset, H Awoye, ... Journal of hydrologic engineering 26 (9), 05021020, 2021 | 19 | 2021 |
| Data-driven vs. physically-based streamflow prediction models M Gauch, J Mai, S Gharari, J Lin Proceedings of the 9th International Workshop on Climate Informatics, Paris …, 2019 | 18 | 2019 |
| Caravan–A global community dataset for large-sample hydrology, Sci. Data, 10, 61 F Kratzert, G Nearing, N Addor, T Erickson, M Gauch, O Gilon, ... | 12 | 2023 |
| In defense of metrics: Metrics sufficiently encode typical human preferences regarding hydrological model performance M Gauch, F Kratzert, O Gilon, H Gupta, J Mai, G Nearing, B Tolson, ... Water Resources Research 59 (6), e2022WR033918, 2023 | 11 | 2023 |
| Conformal prediction for time series with Modern Hopfield Networks A Auer, M Gauch, D Klotz, S Hochreiter Advances in Neural Information Processing Systems 36, 2024 | 10 | 2024 |
| Caravan-A global community dataset for large-sample hydrology, Scientific Data, 10, 61 F Kratzert, G Nearing, N Addor, T Erickson, M Gauch, O Gilon, ... | 9 | 2023 |
| A Data Scientist's Guide to Streamflow Prediction M Gauch, J Lin arXiv preprint arXiv:2006.12975, 2020 | 9 | 2020 |
| Caravan-A global community dataset for large-sample hydrology Sci F Kratzert, G Nearing, N Addor, T Erickson, M Gauch, O Gilon, ... Data 10 (61), 10.1038, 2023 | 8 | 2023 |
| Large-scale river network modeling using Graph Neural Networks F Kratzert, D Klotz, M Gauch, C Klingler, G Nearing, S Hochreiter EGU General Assembly Conference Abstracts, EGU21-13375, 2021 | 7 | 2021 |
| AI Increases Global Access to Reliable Flood Forecasts G Nearing, D Cohen, V Dube, M Gauch, O Gilon, S Harrigan, A Hassidim, ... arXiv preprint arXiv:2307.16104, 2023 | 5 | 2023 |
| Niederschlags-Abfluss-Modellierung mit Long Short-Term Memory (LSTM) F Kratzert, M Gauch, G Nearing, S Hochreiter, D Klotz Österreichische Wasser-und Abfallwirtschaft 73 (7), 270-280, 2021 | 5 | 2021 |
Daniel KlotzJohannes Kepler University Linz, Institute for Machine LearningVerified email at ml.jku.at
