| Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: A case study with the Lorenz 96 model J Brajard, A Carrassi, M Bocquet, L Bertino Journal of computational science 44, 101171, 2020 | 305 | 2020 |
| Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review S Cheng, C Quilodrán-Casas, S Ouala, A Farchi, C Liu, P Tandeo, ... IEEE/CAA Journal of Automatica Sinica 10 (6), 1361-1387, 2023 | 294 | 2023 |
| Bridging observations, theory and numerical simulation of the ocean using machine learning M Sonnewald, R Lguensat, DC Jones, PD Dueben, J Brajard, V Balaji Environmental Research Letters 16 (7), 073008, 2021 | 179 | 2021 |
| Combining data assimilation and machine learning to infer unresolved scale parametrization J Brajard, A Carrassi, M Bocquet, L Bertino Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2021 | 170 | 2021 |
| Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization M Bocquet, J Brajard, A Carrassi, L Bertino arXiv preprint arXiv:2001.06270, 2020 | 163 | 2020 |
| Classification of sea ice types in Sentinel-1 SAR data using convolutional neural networks H Boulze, A Korosov, J Brajard Remote Sensing 12 (13), 2165, 2020 | 157 | 2020 |
| Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models M Bocquet, J Brajard, A Carrassi, L Bertino Nonlinear Processes in Geophysics 26 (3), 143-162, 2019 | 113 | 2019 |
| Learning dynamical systems from partial observations I Ayed, E de Bézenac, A Pajot, J Brajard, P Gallinari arXiv preprint arXiv:1902.11136, 2019 | 111 | 2019 |
| Machine learning for the physics of climate A Bracco, J Brajard, HA Dijkstra, P Hassanzadeh, C Lessig, C Monteleoni Nature Reviews Physics 7 (1), 6-20, 2025 | 83 | 2025 |
| Fusion of rain radar images and wind forecasts in a deep learning model applied to rain nowcasting V Bouget, D Bereziat, J Brajard, A Charantonis, A Filoche Remote Sensing 13 (2), 246, 2021 | 70 | 2021 |
| Use of a neuro-variational inversion for retrieving oceanic and atmospheric constituents from satellite ocean colour sensor: Application to absorbing aerosols J Brajard, C Jamet, C Moulin, S Thiria Neural Networks 19 (2), 178-185, 2006 | 70 | 2006 |
| Twenty-one years of phytoplankton bloom phenology in the Barents, Norwegian, and North Seas E Silva, F Counillon, J Brajard, A Korosov, LH Pettersson, A Samuelsen, ... Frontiers in Marine Science 8, 746327, 2021 | 57 | 2021 |
| Atmospheric correction of MERIS data for case-2 waters using a neuro-variational inversion J Brajard, R Santer, M Crépon, S Thiria Remote Sensing of Environment 126, 51-61, 2012 | 57 | 2012 |
| Super-resolution data assimilation S Barthélémy, J Brajard, L Bertino, F Counillon Ocean Dynamics 72 (8), 661-678, 2022 | 53 | 2022 |
| High performance numerical validation using stochastic arithmetic P Eberhart, J Brajard, P Fortin, F Jézéquel Reliable Computing 21, 35-52, 2015 | 37 | 2015 |
| First evidence of anoxia and nitrogen loss in the southern Canary upwelling system É Machu, X Capet, PA Estrade, S Ndoye, J Brajard, F Baurand, PA Auger, ... Geophysical Research Letters 46 (5), 2619-2627, 2019 | 30 | 2019 |
| Forecasting harmful algae blooms: Application to Dinophysis acuminata in northern Norway E Silva, F Counillon, J Brajard, LH Pettersson, L Naustvoll Harmful Algae 126, 102442, 2023 | 28 | 2023 |
| Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model J Brajard, A Carrassi, M Bocquet, L Bertino Geoscientific Model Development Discussions 2019, 1-21, 2019 | 28 | 2019 |
| Retrieving aerosol characteristics and sea-surface chlorophyll from satellite ocean color multi-spectral sensors using a neural-variational method D Diouf, A Niang, J Brajard, M Crépon, S Thiria Remote Sensing of Environment 130, 74-86, 2013 | 28 | 2013 |
| Silicon cycle in Indian estuaries and its control by biogeochemical and anthropogenic processes KR Mangalaa, D Cardinal, J Brajard, DB Rao, NS Sarma, I Djouraev, ... Continental Shelf Research 148, 64-88, 2017 | 27 | 2017 |
