10 citations · 10 across the 5 of their papers we have counts for
6 papers
Bayesian spatial modelling framework for assessing residential flood risk in property insurance
Mulah Moriah, Franck Vermet, Pierre Ailliot +2
Spatial heterogeneity in insurance risk modelling is often represented using coarse areal structures, which can obscure fine-scale patterns critical for accurate risk assessment. T…
Likelihood-Free Inference for Multivariate Generalized Pareto Models
Samira Aka, Marie Kratz, Philippe Naveau
Likelihood-based inference for multivariate extreme-value models is often unreliable or infeasible when likelihoods are intractable or supports are discrete. This challenge is part…
A sub-asymptotic model for bivariate threshold exceedances
Mirco Lescart, Anna Kiriliouk, Philippe Naveau
Extreme value theory offers a statistical framework for quantifying the risk of rare events, with the generalized Pareto (GP) distribution providing the canonical limit model for u…
Contributions of geolocated weather and building related data for insurance assessment of flood risks
Mulah Moriah, Franck Vermet, Pierre Ailliot +2
Floods rank among the costliest natural hazards, causing over USD 100 billion in insured losses between 2013 and 2023. In France, persistent deficits in the natural catastrophe sch…
Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble Forecasts
Romain Pic, Clément Dombry, Philippe Naveau +1
Accurate precipitation forecasts have a high socio-economic value due to their role in decision-making in various fields such as transport networks and farming. We propose a global…
Proper Scoring Rules for Multivariate Probabilistic Forecasts based on Aggregation and Transformation
Romain Pic, Clément Dombry, Philippe Naveau +1
Proper scoring rules are an essential tool to assess the predictive performance of probabilistic forecasts. However, propriety alone does not ensure an informative characterization…