8 citations · 8 across the 3 of their papers we have counts for
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Modeling Nonstationary Extremal Dependence via Deep Spatial Deformations
Xuanjie Shao, Jordan Richards, Raphael Huser
Modeling nonstationarity that often prevails in extremal dependence of spatial data can be challenging, and typically requires bespoke or complex spatial models that are difficult…
Separation-based causal discovery for extremes
Junshu Jiang, Jordan Richards, Raphaël Huser +1
Structural causal models (SCMs), with an underlying directed acyclic graph (DAG), provide a powerful analytical framework to describe the interaction mechanisms in large-scale comp…
Spatial deformation for non-stationary extremal dependence
Jordan Richards, Jennifer L. Wadsworth
Modelling the extremal dependence structure of spatial data is considerably easier if that structure is stationary. However, for data observed over large or complicated domains, no…