From the 1 of 7 linked papers with an AI index.
7 papers
Spatiotemporally Consistent Multivariate Bias Correction for Climate Projections via Nested Vine Copulas
Theresa Meier, Erwan Koch, Valérie Chavez-Demoulin +1
The paper introduces GN-VBC, a multivariate bias correction method that separates deterministic spatiotemporal effects using GAMs and captures joint dependencies with nested vine c…
Investigating the Robustness of Extreme Precipitation Super-Resolution Across Climates
Louise Largeau, Tom Beucler, David Leutwyler +3
The coarse spatial resolution of gridded climate models, such as general circulation models, limits their direct use in projecting socially relevant variables like extreme precipit…
Identifiability of causal graphs under nonadditive conditionally parametric causal models
Juraj Bodik, Valérie Chavez-Demoulin
Existing approaches to causal discovery often rely on restrictive modeling assumptions that limit their applicability in real-world settings, particularly when data are heavy-taile…
SEMF: Supervised Expectation-Maximization Framework for Predicting Intervals
Ilia Azizi, Marc-Olivier Boldi, Valérie Chavez-Demoulin
This work introduces the Supervised Expectation-Maximization Framework (SEMF), a versatile and model-agnostic approach for generating prediction intervals with any ML model. SEMF e…
Structural restrictions in local causal discovery: identifying direct causes of a target variable
Juraj Bodik, Valérie Chavez-Demoulin
We consider the problem of learning a set of direct causes of a target variable from an observational joint distribution. Learning directed acyclic graphs (DAGs) that represent the…
Tail asymptotics and precise large deviations for some Poisson cluster processes
Fabien Baeriswyl, Valérie Chavez-Demoulin, Olivier Wintenberger
We study the tail asymptotics of two functionals (the maximum and the sum of the marks) of a generic cluster in two sub-models of the marked Poisson cluster process, namely the ren…