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stat.ML2026
Gradient boosting for extremes: sampling theory and application to insurance
Stéphane Lhaut, Olivier Lopez
We develop a statistical learning theory for gradient boosting applied to the estimation of covariate-dependent Generalized Pareto (GP) distributions in the context of Peaks-over-T…
stat.ML2026
Simulation of Multivariate Extremes: a Wasserstein-Aitchison GAN approach
Stéphane Lhaut, Holger Rootzén, Johan Segers
Economically responsible mitigation of multivariate extreme risks-such as extreme rainfall over large areas, large simultaneous variations in many stock prices, or widespread break…