Landslides are nearly ubiquitous phenomena and pose severe threats to people, properties,
and the environment in many areas. Investigators have for long attempted to estimate …

The classical modeling of spatial extremes relies on asymptotic models (ie, max‐stable or r‐
Pareto processes) for block maxima or peaks over high thresholds, respectively. However, at …

Soil clay content is a key parameter that influences many other soil properties and
processes. The potential of adding new and contemporary satellite data for soil property …

This work is motivated by the challenge organized for the 10th International Conference on
Extreme-Value Analysis (EVA2017) to predict daily precipitation quantiles at the 99.8 …

The supplementary material contains the following: a PDF document containing plots for the
inspection of posterior predictive densities, plots showing regionalized predictions, kernel …

We develop a stochastic modeling approach based on spatial point processes of log-
Gaussian Cox type for a collection of around 5000 landslide events provoked by a …

Dengue disease has serious health and socio-economic consequences. Mapping its
occurrence at a fine spatiotemporal scale is a crucial element in the preparation of an early …

There is a growing demand for performing larger-scale Bayesian inference tasks, arising
from greater data availability and higher-dimensional model parameter spaces. In this work …

We apply the tensor train (TT) decomposition to construct the tensor product polynomial
chaos expansion (PCE) of a random field, to solve the stochastic elliptic diffusion PDE with …

Due to climate change and human activity, wildfires are expected to become more frequent
and extreme worldwide, causing economic and ecological disasters. The deployment of …