Retrospective uncertainties for deep models using vine copulas
N Tagasovska, F Ozdemir… - … Conference on Artificial …, 2023 - proceedings.mlr.press
Despite the major progress of deep models as learning machines, uncertainty estimation
remains a major challenge. Existing solutions rely on modified loss functions or architectural …
remains a major challenge. Existing solutions rely on modified loss functions or architectural …
Modeling spatial asymmetries in teleconnected extreme temperatures
Combining strengths from deep learning and extreme value theory can help describe
complex relationships between variables where extreme events have significant impacts …
complex relationships between variables where extreme events have significant impacts …
An Efficient Quasi-Random Sampling for Copulas
This paper examines an efficient method for quasi-random sampling of copulas in Monte
Carlo computations. Traditional methods, like conditional distribution methods (CDM), have …
Carlo computations. Traditional methods, like conditional distribution methods (CDM), have …
Clustered Archimax copulas
S Chatelain, S Perreault, AL Fougères… - Electronic Journal of …, 2025 - projecteuclid.org
Clustered Archimax copulas Page 1 Electronic Journal of Statistics Vol. 19 (2025) 314–360
ISSN: 1935-7524 https://doi.org/10.1214/24-EJS2340 Clustered Archimax copulas Simon …
ISSN: 1935-7524 https://doi.org/10.1214/24-EJS2340 Clustered Archimax copulas Simon …
Modeling Archimedean, Extreme-Value and Archimax Copulas with Neural Networks
Y Ng - 2023 - search.proquest.com
Copulas are popular in high-dimensional statistical applications as they allow for
dependence modeling with arbitrary margins. They are also used in rare event analysis …
dependence modeling with arbitrary margins. They are also used in rare event analysis …