3 papers
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…
q-fin.RM2026
A stochastic SIR model for cyber contagion: application to granular growth of firms and to insurance portfolio
Caroline Hillairet, Olivier Lopez, Lionel Sopgoui
This work evaluates the impact of contagious cyber-events, over a finite horizon, on firms' financial health and on a cyber insurance portfolio. Our approach builds on key empirica…
stat.ML2025
WTNN: Weibull-Tailored Neural Networks for survival analysis
Gabrielle Rives, Olivier Lopez, Nicolas Bousquet
The Weibull distribution is a commonly adopted choice for modeling the survival of systems subject to maintenance over time. When only proxy indicators and censored observations ar…