3 citations · 5 across the 4 of their papers we have counts for
4 papers
Model selection for extremal dependence structures using deep learning: Application to environmental data
Manaf Ahmed, Véronique Maume-Deschamps, Pierre Ribereau
This paper introduces a new methodology for extreme spatial dependence structure selection. It is based on deep learning techniques, specifically Convolutional Neural Networks -CNN…
Recognizing a Spatial Extreme dependence structure: A Deep Learning approach
Manaf Ahmed, Véronique Maume-Deschamps, Pierre Ribereau
Understanding the behaviour of environmental extreme events is crucial for evaluating economic losses, assessing risks, health care and many other aspects. In the spatial context,…
A semi-parametric estimation for max-mixture spatial processes
M. Ahmed, V Maume-Deschamps, P. Ribereau +1
We proposed a semi-parametric estimation procedure in order to estimate the parameters of a max-mixture model and also of a max-stable model (inverse max-stable model) as an altern…
Spatial risk measure for gaussian processes
M Ahmed, V Maume-Deschamps, P Ribereau +1
In this paper, we study the quantitative behavior of a spatial risk measure corresponding to a damage function and a region, taking into account the spatial dependence of the under…