479 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR192 papers
- Université Paris-SaclayFR78 papers
- Université de MontpellierFR75 papers
- AgroParisTechFR59 papers
- Centre de Coopération Internationale en Recherche Agronomique pour le DéveloppementFR56 papers
- Mathématiques, Informatique et Statistique pour l'Environnement et l'AgronomieFR44 papers
- Institut de Recherche pour le DéveloppementFR41 papers
- Institut National de la Recherche AgronomiqueMA39 papers
- Institut Agro MontpellierFR38 papers
- Institut national de recherche en sciences et technologies du numériqueFR38 papers
- Territoires, Environnement, Télédétection et Information SpatialeFR33 papers
- Université Grenoble AlpesFR32 papers
4 papers · 2 filters
High-dimensional modeling of spatial and spatio-temporal conditional extremes using INLA and Gaussian Markov random fields
Emma S. Simpson, Thomas Opitz, Jennifer L. Wadsworth
The conditional extremes framework allows for event-based stochastic modeling of dependent extremes, and has recently been extended to spatial and spatio-temporal settings. After s…
Modeling dependent survival data through random effects with spatial correlation at the subject level
Ajmal Oodally, Estelle Kuhn, Klara Goethals +1
Dynamical phenomena such as infectious diseases are often investigated by following up subjects longitudinally, thus generating time to event data. The spatial aspect of such data…
A variable selection approach for highly correlated predictors in high-dimensional genomic data
Wencan Zhu, Céline Lévy-Leduc, Nils Ternès
In genomic studies, identifying biomarkers associated with a variable of interest is a major concern in biomedical research. Regularized approaches are classically used to perform…
Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise
Gaetano Romano, Guillem Rigaill, Vincent Runge +1
Whilst there are a plethora of algorithms for detecting changes in mean in univariate time-series, almost all struggle in real applications where there is autocorrelated noise or w…