2 citations · 2 across the 3 of their papers we have counts for
4 papers
Transfer learning for causal forest
Bérénice-Alexia Jocteur, Véronique Maume-Deschamps, Pierre Ribereau
Transfer learning addresses the challenge of transfering knowledge from one domain to another. Traditional transfer learning focuses on adapting models trained on a source domain (…
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…
Spatial Risk Measure for Max-Stable and Max-Mixture Processes
Ahmed Manaf, Véronique Maume-Deschamps, Pierre Ribereau +1
In this paper, we consider isotropic and stationary max-stable, inverse max-stable and max-mixture processes $X=(X(s))\_{s\in\bR^2}$ and the damage function $\cD\_X^ν= |X|^ν$ with…
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…