Web: http://arxiv.org/abs/2205.01224

May 4, 2022, 1:11 a.m. | Andrew McDonald, Pang-Ning Tan, Lifeng Luo

cs.LG updates on arXiv.org arxiv.org

Normalizing flows, a popular class of deep generative models, often fail to
represent extreme phenomena observed in real-world processes. In particular,
existing normalizing flow architectures struggle to model multivariate
extremes, characterized by heavy-tailed marginal distributions and asymmetric
tail dependence among variables. In light of this shortcoming, we propose COMET
(COpula Multivariate ExTreme) Flows, which decompose the process of modeling a
joint distribution into two parts: (i) modeling its marginal distributions, and
(ii) modeling its copula distribution. COMET Flows capture heavy-tailed …

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