1 citations · 1 across the 5 of their papers we have counts for
5 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…
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…
FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing Flows and the Feynman-Kac Formula
Naoufal El Bekri, Lucas Drumetz, Franck Vermet
Solving the Fokker-Planck equation for high-dimensional complex dynamical systems remains a pivotal yet challenging task due to the intractability of analytical solutions and the l…
Time-changed normalizing flows for accurate SDE modeling
Naoufal El Bekri, Lucas Drumetz, Franck Vermet
The generative paradigm has become increasingly important in machine learning and deep learning models. Among popular generative models are normalizing flows, which enable exact li…
Measuring and Mitigating Biases in Motor Insurance Pricing
Mulah Moriah, Franck Vermet, Arthur Charpentier
The non-life insurance sector operates within a highly competitive and tightly regulated framework, confronting a pivotal juncture in the formulation of pricing strategies. Insurer…