most citedDeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

cs.LG2022★ 1 cited

DeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data

Asadullah Hill Galib, Andrew McDonald, Tyler Wilson +2

Accurate forecasting of extreme values in time series is critical due to the significant impact of extreme events on human and natural systems. This paper presents DeepExtrema, a n…

cs.LG2022

COMET Flows: Towards Generative Modeling of Multivariate Extremes and Tail Dependence

Andrew McDonald, Pang-Ning Tan, Lifeng Luo

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 a…