143 citations · 145 across the 8 of their papers we have counts for
11 papers
EM algorithm for generalized Ridge regression with spatial covariates
Said Obakrim, Pierre Ailliot, Valérie Monbet +1
The generalized Ridge penalty is a powerful tool for dealing with overfitting and for high-dimensional regressions. The generalized Ridge regression can be derived as the mean of a…
Learning the spatio-temporal relationship between wind and significant wave height using deep learning
Said Obakrim, Valérie Monbet, Nicolas Raillard +1
Ocean wave climate has a significant impact on near-shore and off-shore human activities, and its characterisation can help in the design of ocean structures such as wave energy co…
An algorithm for non-parametric estimation in state-space models
Thi Tuyet Trang Chau, Pierre Ailliot, Valérie Monbet
State-space models are ubiquitous in the statistical literature since they provide a flexible and interpretable framework for analyzing many time series. In most practical applicat…
A Review of Innovation-Based Methods to Jointly Estimate Model and Observation Error Covariance Matrices in Ensemble Data Assimilation
Pierre Tandeo, Pierre Ailliot, Marc Bocquet +4
Data assimilation combines forecasts from a numerical model with observations. Most of the current data assimilation algorithms consider the model and observation error terms as ad…
An efficient particle-based method for maximum likelihood estimation in nonlinear state-space models
Thi Tuyet Trang Chau, Pierre Ailliot, Valérie Monbet +1
Data assimilation methods aim at estimating the state of a system by combining observations with a physical model. When sequential data assimilation is considered, the joint distri…
Locally-adapted convolution-based super-resolution of irregularly-sampled ocean remote sensing data
Manuel López-Radcenco, Ronan Fablet, Abdeldjalil Aïssa-El-Bey +1
Super-resolution is a classical problem in image processing, with numerous applications to remote sensing image enhancement. Here, we address the super-resolution of irregularly-sa…
Dependent time changed processes with applications to nonlinear ocean waves
Pierre Ailliot, Bernard Delyon, Valérie Monbet +1
Many records in environmental sciences exhibit asymmetric trajectories and there is a need for simple and tractable models which can reproduce such features. In this paper we explo…
Gaussian linear state-space model for wind fields in the North-East Atlantic
Julie Bessac, Pierre Ailliot, Valerie Monbet
A space-time model for wind fields is proposed. It aims at simulating realistic wind conditions with a focus on reproducing the space-time motions of the meteorological systems. A…
Consistency of the maximum likelihood estimate for Non-homogeneous Markov-switching models
Pierre Ailliot, Francoise Pene
Many nonlinear time series models have been proposed in the last decades. Among them, the models with regime switchings provide a class of versatile and interpretable models which…
Modeling the Coastal Ocean over a Time Period of Several Weeks
Pierre Ailliot, Emmanuel Frenod, Valerie Monbet
From a scale analysis of hydrodynamic phenomena having a significant action on the drift of an object in coastal ocean waters, we deduce equations modeling the associated hydrodyna…
Long term object drift in the ocean with tide and wind
Pierre Ailliot, Emmanuel Frenod, Valerie Monbet
In this paper, we propose a new method to forecast the drift of objects in near coastal ocean on a period of several weeks. The proposed approach consists in estimating the probabi…