6 citations · 17 across the 6 of their papers we have counts for
7 papers
A Geometric Framework for the Bayesian Estimation of Joint Environmental Extremes
Reetam Majumder, Callum J. R. Murphy-Barltrop
Multivariate extreme events tend to have broader impacts on society compared to individual extremes. Flexible and accurate modeling of multivariate extremes is therefore crucial fo…
Generative Machine Learning for Multivariate Angular Simulation
Jakob Benjamin Wessel, Callum J. R. Murphy-Barltrop, Emma S. Simpson
With the recent development of new geometric and angular-radial frameworks for multivariate extremes, reliably simulating from angular variables in moderate-to-high dimensions is o…
Deep learning joint extremes of metocean variables using the SPAR model
Ed Mackay, Callum Murphy-Barltrop, Jordan Richards +1
This paper presents a novel deep learning framework for estimating multivariate joint extremes of metocean variables, based on the Semi-Parametric Angular-Radial (SPAR) model. When…
Deep Learning of Multivariate Extremes via a Geometric Representation
Callum J. R. Murphy-Barltrop, Reetam Majumder, Jordan Richards
The study of geometric extremes, where extremal dependence properties are inferred from the deterministic limiting shapes of scaled sample clouds, provides an exciting approach to…
Inference for bivariate extremes via a semi-parametric angular-radial model
Callum John Rowlandson Murphy-Barltrop, Ed Mackay, Philip Jonathan
The modelling of multivariate extreme events is important in a wide variety of applications, including flood risk analysis, metocean engineering and financial modelling. A wide var…
Extreme value methods for estimating rare events in Utopia
L. M. André, R. Campbell, E. D'Arcy +6
To capture the extremal behaviour of complex environmental phenomena in practice, flexi\-ble techniques for modelling tail behaviour are required. In this paper, we introduce a var…
A marginal modelling approach for predicting wildfire extremes across the contiguous United States
Eleanor D'Arcy, Callum John Rowlandson Murphy-Barltrop, Rob Shooter +1
This paper details a methodology proposed for the EVA 2021 conference data challenge. The aim of this challenge was to predict the number and size of wildfires over the contiguous…