| Deep learning rainfall–runoff predictions of extreme events JM Frame, F Kratzert, D Klotz, M Gauch, G Shalev, O Gilon, LM Qualls, ... Hydrology and Earth System Sciences 26 (13), 3377-3392, 2022 | 90 | 2022 |
| Flood forecasting with machine learning models in an operational framework S Nevo, E Morin, A Gerzi Rosenthal, A Metzger, C Barshai, D Weitzner, ... Hydrology and Earth System Sciences 26 (15), 4013-4032, 2022 | 81 | 2022 |
| Caravan-A global community dataset for large-sample hydrology F Kratzert, G Nearing, N Addor, T Erickson, M Gauch, O Gilon, ... Scientific Data 10 (1), 61, 2023 | 43 | 2023 |
| Customization scenarios for de-identification of clinical notes T Hartman, MD Howell, J Dean, S Hoory, R Slyper, I Laish, O Gilon, ... BMC medical informatics and decision making 20, 1-9, 2020 | 40 | 2020 |
| Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks GS Nearing, D Klotz, AK Sampson, F Kratzert, M Gauch, JM Frame, ... Hydrology and earth system sciences discussions 2021, 1-25, 2021 | 29 | 2021 |
| A joint named-entity recognizer for heterogeneous tag-sets using a tag hierarchy G Beryozkin, Y Drori, O Gilon, T Hartman, I Szpektor arXiv preprint arXiv:1905.09135, 2019 | 24 | 2019 |
| 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 | 20 | 2021 |
| 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, ... | 13 | 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 | 12 | 2023 |
| 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, ... | 12 | 2023 |
| Buffer management for packets with processing times Y Azar, O Gilon Algorithms-ESA 2015: 23rd Annual European Symposium, Patras, Greece …, 2015 | 9 | 2015 |
| 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 |
| 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 |
| ML-based flood forecasting: Advances in scale, accuracy and reach S Nevo, G Elidan, A Hassidim, G Shalev, O Gilon, G Nearing, Y Matias arXiv preprint arXiv:2012.00671, 2020 | 5 | 2020 |
| Global prediction of extreme floods in ungauged watersheds G Nearing, D Cohen, V Dube, M Gauch, O Gilon, S Harrigan, A Hassidim, ... Nature 627 (8004), 559-563, 2024 | 4 | 2024 |
| Towards flood warnings everywhere-data-driven rainfall-runoff modeling at global scale F Kratzert, M Gauch, D Klotz, A Metzger, G Nearing, G Shalev, S Shenzis, ... AGU Fall Meeting Conference Abstracts, Pp. GC12A 4, 2022 | 3 | 2022 |
| Scheduling with deadlines and buffer management with processing requirements Y Azar, O Gilon Algorithmica 78, 1246-1262, 2017 | 2 | 2017 |
| From Hindcast to Forecast with Deep Learning Streamflow Models G Nearing, M Gauch, D Klotz, F Kratzert, A Metzger, G Shalev, S Shenzis, ... EGU General Assembly Conference Abstracts, EGU-16974, 2023 | 1 | 2023 |
| Kidney exchange with multiple donors O Gilon, T Gilon, A Romm Available at SSRN 3451470, 2019 | 1 | 2019 |
| Deep Learning for Spatially Distributed Rainfall–Runoff Modeling M Gauch, F Kratzert, V Dube, O Gilon, D Klotz, A Metzger, G Nearing, ... EGU24, 2024 | | 2024 |
