M-CaStLe generalizes local stencil-based causal discovery to the multivariate case and decomposes resulting graphs into reaction and spatial components for interpretation in space-time gridded data.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
A non-stationary Markov process with bivariate extreme value theory attributes full heatwave time series over Europe to anthropogenic forcing via likelihood ratios between ERA5 and CMIP6 runs, finding strong evidence since the 1970s but no signal beyond mean temperature increase.
citing papers explorer
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M-CaStLe: Uncovering Local Causal Structures in Multivariate Space-Time Gridded Data
M-CaStLe generalizes local stencil-based causal discovery to the multivariate case and decomposes resulting graphs into reaction and spatial components for interpretation in space-time gridded data.
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Non-stationary time series attribution for heatwaves over Europe
A non-stationary Markov process with bivariate extreme value theory attributes full heatwave time series over Europe to anthropogenic forcing via likelihood ratios between ERA5 and CMIP6 runs, finding strong evidence since the 1970s but no signal beyond mean temperature increase.