3 citations · 6 across the 16 of their papers we have counts for
5 papers · 1 filter
Statistics of Extremes for Neuroscience
Paolo V. Redondo, Matheus B. Guerrero, Raphaël Huser +1
This chapter illustrates how tools from univariate and multivariate statistics of extremes can complement classical methods used to study brain signals and enhance the understandin…
Statistics of extremes for natural hazards: landslides and earthquakes
Rishikesh Yadav, Luigi Lombardo, Raphaël Huser
In this chapter, we illustrate the use of split bulk-tail models and subasymptotic models motivated by extreme-value theory in the context of hazard assessment for earthquake-induc…
Extreme quantile regression with deep learning
Jordan Richards, Raphaël Huser
Estimation of extreme conditional quantiles is often required for risk assessment of natural hazards in climate and geo-environmental sciences and for quantitative risk management…
Modeling of spatial extremes in environmental data science: Time to move away from max-stable processes
Raphaël Huser, Thomas Opitz, Jennifer Wadsworth
Environmental data science for spatial extremes has traditionally relied heavily on max-stable processes. Even though the popularity of these models has perhaps peaked with statist…
At the junction between deep learning and statistics of extremes: formalizing the landslide hazard definition
Ashok Dahal, Raphaël Huser, Luigi Lombardo
The most adopted definition of landslide hazard combines spatial information about landslide location (susceptibility), threat (intensity), and frequency (return period). Only the…