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08/10/2023
Exploring the Efficacy of Statistical and Deep Learning Methods for Large Spatial Datasets: A Case Study
Increasingly large and complex spatial datasets pose massive inferential...
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05/20/2022
Joint modeling of landslide counts and sizes using spatial marked point processes with sub-asymptotic mark distributions
To accurately quantify landslide hazard in a region of Turkey, we develo...
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12/30/2021
A combined statistical and machine learning approach for spatial prediction of extreme wildfire frequencies and sizes
Motivated by the Extreme Value Analysis 2021 (EVA 2021) data challenge w...
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12/17/2021
A flexible Bayesian hierarchical modeling framework for spatially dependent peaks-over-threshold data
In this work, we develop a constructive modeling framework for extreme t...
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12/10/2019
Spatial hierarchical modeling of threshold exceedances using rate mixtures
We develop new flexible univariate models for light-tailed and heavy-tai...
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11/19/2019