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stat.ME2026
Calibrating simplified vine copulas with a noise contrastive estimation approach
Michael Denis Kraus, David Huk, Claudia Czado
Vine copulas provide a flexible framework for modeling complex multivariate dependence structures using only bivariate building blocks. Their practical success relies heavily on th…
stat.ME2025
Probabilistic Rainfall Downscaling: Joint Generalized Neural Models with Censored Spatial Gaussian Copula
David Huk, Rilwan A. Adewoyin, Ritabrata Dutta
This work introduces a novel approach for generating conditional probabilistic rainfall forecasts with temporal and spatial dependence. A two-step procedure is employed. Firstly, m…
stat.ME2025
Your copula is a classifier in disguise: classification-based copula density estimation
David Huk, Mark Steel, Ritabrata Dutta
We propose reinterpreting copula density estimation as a discriminative task. Under this novel estimation scheme, we train a classifier to distinguish samples from the joint densit…