bias correction 1climate projections 1multivariate analysis 1spatiotemporal modeling 1vine copulas 1
From the 1 of 3 linked papers with an AI index.
3 papers
stat.ME2026
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…
stat.ME2026
Throwing Vines at the Wall: Structure Learning via Random Search
Thibault Vatter, Thomas Nagler
Vine copulas offer flexible multivariate dependence modeling and have become widely used in machine learning. Yet, structure learning remains a key challenge. Early heuristics, suc…
cs.LG2025
Vine Copulas as Differentiable Computational Graphs
Tuoyuan Cheng, Thibault Vatter, Thomas Nagler +1
Vine copulas are sophisticated models for multivariate distributions and are increasingly used in machine learning. To facilitate their integration into modern ML pipelines, we int…