218 citations · 323 across the 27 of their papers we have counts for
34 papers
Spatial Prediction with Guided Diffusion
Andrew Zammit-Mangion, Lachlan Astfalck, Raphaël Huser +2
Spatial prediction is a critically important task in data analyses that involve spatially or spatio-temporally-referenced data. It is commonly carried out using hierarchical models…
Neural Bayes estimation and selection for complex bivariate extremal dependence models
Lídia M. André, Jennifer L. Wadsworth, Raphaël Huser
Likelihood-free approaches are appealing for performing inference on complex dependence models, either because it is not possible to formulate a likelihood function, or its evaluat…
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…
Patterns in Spatio-Temporal Extremes
Marco Oesting, Raphaël Huser
In environmental science applications, extreme events frequently exhibit a complex spatio-temporal structure, which is difficult to describe flexibly and estimate in a computationa…
Spatial modeling and future projection of extreme precipitation extents
Peng Zhong, Manuela Brunner, Thomas Opitz +1
Extreme precipitation events with large spatial extents may have more severe impacts than localized events as they can lead to widespread flooding. It is debated how climate change…
Insights into the drivers and spatio-temporal trends of extreme Mediterranean wildfires with statistical deep-learning
Jordan Richards, Raphaël Huser, Emanuele Bevacqua +1
Extreme wildfires are a significant cause of human death and biodiversity destruction within countries that encompass the Mediterranean Basin. Recent worrying trends in wildfire ac…