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08/28/2023
Deep graphical regression for jointly moderate and extreme Australian wildfires
Recent wildfires in Australia have led to considerable economic loss and...
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08/07/2023
Spatial wildfire risk modeling using mixtures of tree-based multivariate Pareto distributions
Wildfires pose a severe threat to the ecosystem and economy, and risk as...
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07/28/2023
Extremal Dependence of Moving Average Processes Driven by Exponential-Tailed Lévy Noise
Moving average processes driven by exponential-tailed Lévy noise are imp...
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07/21/2023
Fast spatial simulation of extreme high-resolution radar precipitation data using INLA
We develop a methodology for modelling and simulating high-dimensional s...
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06/27/2023
Likelihood-free neural Bayes estimators for censored inference with peaks-over-threshold models
Inference for spatial extremal dependence models can be computationally ...
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03/11/2023
Measuring Information Transfer Between Nodes in a Brain Network through Spectral Transfer Entropy
Brain connectivity reflects how different regions of the brain interact ...
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12/21/2022
Patterns in Spatio-Temporal Extremes
In environmental science applications, extreme events frequently exhibit...
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12/08/2022
Club Exco: clustering brain extreme communities from multi-channel EEG data
Current methods for clustering nodes over time in a brain network are de...
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12/06/2022
Spatial modeling and future projection of extreme precipitation extents
Extreme precipitation events with large spatial extents may have more se...
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12/04/2022
Insights into the drivers and spatio-temporal trends of extreme Mediterranean wildfires with statistical deep-learning
Extreme wildfires continue to be a significant cause of human death and ...
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10/13/2022
Partial Tail-Correlation Coefficient Applied to Extremal-Network Learning
We propose a novel extremal dependence measure called the partial tail-c...
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10/11/2022
Flexible Modeling of Nonstationary Extremal Dependence Using Spatially-Fused LASSO and Ridge Penalties
Statistical modeling of a nonstationary spatial extremal dependence stru...
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10/03/2022
An Efficient Workflow for Modelling High-Dimensional Spatial Extremes
A successful model for high-dimensional spatial extremes should, in prin...
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08/27/2022
Fast Optimal Estimation with Intractable Models using Permutation-Invariant Neural Networks
Neural networks have recently shown promise for likelihood-free inferenc...
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08/16/2022
A unifying partially-interpretable framework for neural network-based extreme quantile regression
Risk management in many environmental settings requires an understanding...
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07/30/2022
Functional-Coefficient Models for Multivariate Time Series in Designed Experiments: with Applications to Brain Signals
To study the neurophysiological basis of attention deficit hyperactivity...
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06/22/2022
Flexible Modeling of Multivariate Spatial Extremes
We develop a novel multi-factor copula model for multivariate spatial ex...
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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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03/10/2022
Vecchia Likelihood Approximation for Accurate and Fast Inference in Intractable Spatial Extremes Models
Max-stable processes are the most popular models for high-impact spatial...
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02/14/2022
Joint Modeling and Prediction of Massive Spatio-Temporal Wildfire Count and Burnt Area Data with the INLA-SPDE Approach
This paper describes the methodology used by the team RedSea in the data...
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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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12/19/2021
Realistic and Fast Modeling of Spatial Extremes over Large Geographical Domains
Various natural phenomena exhibit spatial extremal dependence at short d...
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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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10/06/2021
Latent Gaussian Models for High-Dimensional Spatial Extremes
In this chapter, we show how to efficiently model high-dimensional extre...
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06/24/2021
Practical strategies for GEV-based regression models for extremes
The generalised extreme value (GEV) distribution is a three parameter fa...
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05/11/2021
Modeling spatial extremes using normal mean-variance mixtures
Classical models for multivariate or spatial extremes are mainly based u...
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02/28/2021
Exact Simulation of Max-Infinitely Divisible Processes
Max-infinitely divisible (max-id) processes play a central role in extre...
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02/14/2021
Modeling Spatial Data with Cauchy Convolution Processes
We study the class of models for spatial data obtained from Cauchy convo...
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01/06/2021
Tractable Bayes of Skew-Elliptical Link Models for Correlated Binary Data
Correlated binary response data with covariates are ubiquitous in longit...
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01/03/2021
Conex-Connect: Learning Patterns in Extremal Brain Connectivity From Multi-Channel EEG Data
Epilepsy is a chronic neurological disorder affecting more than 50 milli...
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07/01/2020
Advances in Statistical Modeling of Spatial Extremes
The classical modeling of spatial extremes relies on asymptotic models (...
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06/14/2020
High-resolution Bayesian mapping of landslide hazard with unobserved trigger event
Statistical models for landslide hazard enable mapping of risk factors a...
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06/02/2020
Assessing Non-Stationary Heatwave Hazard with Magnitude-Dependent Spatial Extremal Dependence
The modeling of spatio-temporal trends in temperature extremes can help ...
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12/11/2019
Estimating high-resolution Red sea surface temperature hotspots, using a low-rank semiparametric spatial model
In this work, we estimate extreme sea surface temperature (SST) hotspots...
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12/11/2019
A low-rank semiparametric Bayesian spatial model for estimating extreme Red Sea surface temperature hotspots
In this work, we focus on estimating sea surface temperature (SST) hotsp...
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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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12/03/2019
Space-Time Landslide Predictive Modelling
Landslides are nearly ubiquitous phenomena and pose severe threats to pe...
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12/02/2019
Editorial: EVA 2019 data competition on spatio-temporal prediction of Red Sea surface temperature extremes
Large, non-stationary spatio-temporal data are ubiquitous in modern stat...
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07/27/2019
Max-and-Smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models
With modern high-dimensional data, complex statistical models are necess...
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07/10/2019
Approximate Bayesian inference for spatial flood frequency analysis
Extreme floods cause casualties, widespread property damage, and damage ...
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05/13/2019
Asymmetric tail dependence modeling, with application to cryptocurrency market data
Since the inception of Bitcoin in 2008, cryptocurrencies have played an ...
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10/09/2018
A three-stage model for short-term extreme wind speed probabilistic forecasting
Renewable sources of energy such as wind power have become a sustainable...
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07/23/2018
Geostatistical modeling to capture seismic-shaking patterns from earthquake-induced landslides
In this paper, we investigate earthquake-induced landslides using a geos...
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05/16/2018
A Hierarchical Max-infinitely Divisible Process for Extreme Areal Precipitation Over Watersheds
Understanding the spatial extent of extreme precipitation is necessary f...
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03/18/2018
Bayesian Modeling of Air Pollution Extremes Using Nested Multivariate Max-Stable Processes
Capturing the potentially strong dependence among the peak concentration...
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02/04/2018
INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles
This work has been motivated by the challenge of the 2017 conference on ...
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01/09/2018
Penultimate modeling of spatial extremes: statistical inference for max-infinitely divisible processes
Extreme-value theory for stochastic processes has motivated the statisti...
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10/02/2017