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20082026
most citedSingle index regression models in the presence of censoring depending on the covariates

23 citations · 29 across the 9 of their papers we have counts for

collaborators

10 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…

stat.AP2023

Parametric insurance for extreme risks: the challenge of properly covering severe claims

Olivier Lopez, Maud Thomas

Parametric insurance has emerged as a practical way to cover risks that may be difficult to assess. By introducing a parameter that triggers compensation and allows the insurer to…

math.ST2021★ 2 cited

Generalized Pareto Regression Trees for extreme events analysis

Sébastien Farkas, Antoine Heranval, Olivier Lopez +1

In this paper, we provide finite sample results to assess the consistency of Generalized Pareto regression trees, as tools to perform extreme value regression. The results that we…

math.ST2015★ 4 cited

Single-index copulae

Jean-David Fermanian, Olivier Lopez

We introduce so-called "single-index copulae". They are semi-parametric conditional copulae whose parameter is an unknown "link" function of a univariate index only. We provide est…