3 papers
stat.ML2026
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 (…
physics.data-an2024
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…
math.ST2017
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…