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network or crashes of the stock market, current approaches for structural causal modeling in extremes are limited to scenarios where all variables are simultaneously large. Such assumptions are often
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. However, when interest is rather in the behavior of the system during extreme events, for example during floods in a river network or crashes of the stock market, current approaches for structural causal
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spatial region and, in many applications, over time. Examples include the positions of trees in a forest, disease cases in epidemiology, crime incidents in cities, traffic events on transportation networks
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