| Calibrated ensemble forecasts using quantile regression forests and ensemble model output statistics M Taillardat, O Mestre, M Zamo, P Naveau Monthly Weather Review 144 (6), 2375-2393, 2016 | 264 | 2016 |
| Statistical postprocessing for weather forecasts: Review, challenges, and avenues in a big data world S Vannitsem, JB Bremnes, J Demaeyer, GR Evans, J Flowerdew, S Hemri, ... Bulletin of the American Meteorological Society 102 (3), E681-E699, 2021 | 253 | 2021 |
| Forest-based and semiparametric methods for the postprocessing of rainfall ensemble forecasting M Taillardat, AL Fougères, P Naveau, O Mestre Weather and Forecasting 34 (3), 617-634, 2019 | 74* | 2019 |
| From research to applications–examples of operational ensemble post-processing in France using machine learning M Taillardat, O Mestre Nonlinear Processes in Geophysics 27 (2), 329-347, 2020 | 42 | 2020 |
| Evaluating probabilistic forecasts of extremes using continuous ranked probability score distributions M Taillardat, AL Fougères, P Naveau, R De Fondeville International Journal of Forecasting 39 (3), 1448-1459, 2023 | 37* | 2023 |
| The EUPPBench postprocessing benchmark dataset v1. 0 J Demaeyer, J Bhend, S Lerch, C Primo, B Van Schaeybroeck, A Atencia, ... Earth System Science Data 15 (6), 2635-2653, 2023 | 26 | 2023 |
| Calibrated ensemble forecasts of the height of new snow using quantile regression forests and ensemble model output statistics G Evin, M Lafaysse, M Taillardat, M Zamo Nonlinear Processes in Geophysics 28 (3), 467-480, 2021 | 16 | 2021 |
| Strategies for hydrologic ensemble generation and calibration: On the merits of using model-based predictors AL Tiberi-Wadier, N Goutal, S Ricci, P Sergent, M Taillardat, F Bouttier, ... Journal of Hydrology 599, 126233, 2021 | 13 | 2021 |
| Distributional regression and its evaluation with the CRPS: Bounds and convergence of the minimax risk R Pic, C Dombry, P Naveau, M Taillardat International Journal of Forecasting 39 (4), 1564-1572, 2023 | 10* | 2023 |
| Non-parametric Methods of post-processing for Ensemble Forecasting M Taillardat Université Paris Saclay (COmUE), 2017 | 9* | 2017 |
| Skewed and mixture of Gaussian distributions for ensemble postprocessing M Taillardat Atmosphere 12 (8), 966, 2021 | 8 | 2021 |
| Mathematical Properties of Continuous Ranked Probability Score Forecasting C Dombry, R Pic, P Naveau, M Taillardat EGU General Assembly Conference Abstracts, EGU-11230, 2023 | 1 | 2023 |
| Vers une approche ensembliste de la prévision des crues AL Tiberi-Wadier, M Taillardat, N Goutal, S Ricci, P Sergent, F Bouttier, ... De la prévision des crues à la gestion de crise, 2018 | 1 | 2018 |
| Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble Forecasts R Pic, C Dombry, P Naveau, M Taillardat arXiv preprint arXiv:2407.02125, 2024 | | 2024 |
| Proper Scoring Rules for Multivariate Probabilistic Forecasts based on Aggregation and Transformation R Pic, C Dombry, P Naveau, M Taillardat arXiv preprint arXiv:2407.00650, 2024 | | 2024 |
| U-Net based Methods for the Postprocessing of Precipitation Ensemble Forecasting R Pic, C Dombry, M Taillardat, P Naveau EGU General Assembly Conference Abstracts, EGU-2592, 2023 | | 2023 |
| The EUPPBench postprocessing benchmark J Bhend, J Demaeyer, S Lerch, C Primo, B Van Schaeybroeck, A Atencia, ... EGU General Assembly Conference Abstracts, EGU-9328, 2023 | | 2023 |
| The EUPPBench postprocessing benchmark dataset J Demaeyer, J Bhend, S Lerch, C Primo, B Van Schaeybroeck, A Atencia, ... EMS Annual Meeting, 2023 | | 2023 |
| Preface: Advances in post-processing and blending of deterministic and ensemble forecasts S Hemri, S Lerch, M Taillardat, S Vannitsem, DS Wilks Nonlinear Processes in Geophysics 27 (4), 519-521, 2020 | | 2020 |