News
- Bridging classical data assimilation and optimal transport
- Sea ice data assimilation with a complex rheology
- Inverse modelling of CO2 plume emissions with deep learning
- Machine learning emulation of sea-ice melt ponds
- Deep learning surrogate model of the Arctic sea ice
- Bayesian inversion of the emission of a large urban fire
- Tenure-track professor position at Cerea!
- Deep learning of subgrid-scale parametrisations for sea ice
- Nonlocal metrics for atmospheric gas plumes comparison
- A review of combined data assimilation, machine learning and uncertainty quantification
- Surrogate modelling in the climate sciences
- Bayesian transdimensional inversion of the Fukushima Daiichi caesium 137 release
- A fast, single-iteration ensemble Kalman smoother for sequential data assimilation
- Online learning of state variables, global and local parameters with an EnKF
- Data assimilation and chaos: an overview
- Online model error correction with 4D-Var and machine learning
- Uncertainty quantification for the autumn 2017 Ru-106 atmospheric dispersion event
- Using machine learning to correct model error in data assimilation and forecast applications
- Editorial: Data assimilation of nonlocal observations in complex systems
PhD and Postdoc positions on Machine Learning and Data Assimilation applied to sea-ice modeling- Data assimilation and machine learning to infer unresolved scale parametrization
- Improving numerical dispersion modelling in built environments with the IEnKS
- Thèse CEA: Assimilation de données infrason provenant de la houle océanique.
- Online (sequential) learning of chaotic models with augmented EnKFs
- A review of methods to estimate R and Q in ensemble data assimilation
- Reconstruction of the autumn 2017 Ruthenium-106 atmospheric contamination source
- Combining ML and DA for the inference of chaotic dynamics
- Ensemble data assimilation applied to the COVID-19 pandemic
- On temporal scale separation in coupled data assimilation with the EnKF
- On the numerical integration of the stochastic Lorenz-96 model
- Bayesian data-driven inference of chaotic dynamics
- An iterative ensemble Kalman smoother in presence of additive model error
- Slides of the Big data, data assimilation and UQ course at IHP
- Big data, data assimilation and UQ course at IHP, Paris in late October!
- Model error estimation for CO2 inversions using an advanced regularisation of ensemble outputs
- Data driven reconstruction of chaotic dynamics using data assimilation techniques
- A more consistent update scheme for the local EnKF!
- EGU general assembly short course on data assimilation 2019: the slides!
- Data assimilation at local scale to improve CFD simulations - 3D case and real observations
- Adaptive covariance inflation in the ensemble Kalman filter by Gaussian scale mixtures
- Efficient localisation of the local ensemble square root Kalman filter
- ECMWF Fellowship
- Local particle filter for geofluid models: a review and beyond
- Data assimilation at local scale to improve CFD simulations
- Assimilation in the Unstable Subspace and additive model error, part II
- Assimilation in the Unstable Subspace and additive model error, part I
- A data assimilation overview for the climatologists (and other curious geophysicists)
- Towards an ensemble Kalman filter without the need for an ensemble...
- 15-16 May in Toulouse: A tribute to O. Talagrand and G. Desroziers!
- EGU general assembly short course on data assimilation: the slides!
- Quasi static ensemble variational data assimilation
- Stochastic parameterization identification using ensemble Kalman filtering combined with maximum likelihood methods
- Asynchronous data assimilation with the EnKF in presence of additive model error (AEnKF-Q)
- The iterative ensemble Kalman filter with additive model error (IEnKF-Q)
- Uncertainty quantification of the best estimate from an inverse problem
- On the representation error in data assimilation
- EnKF with an isopycnal ocean model
- Model dynamics and 4D-En-Var methods
- Model dynamics and the (ensemble) Kalman filter: published!
- Data assimilation: Methods, Algorithms and Applications: Our book is out!
- Model dynamics and the (ensemble) Kalman filter
- Using data assimilation to compute model evidence
- Using optimal transport for the verification of plumes of pollutant
- Data assimilation for the detection and attribution in climate sciences