5 papers
Diagnostic Tools for Extreme Value Regression Models
Ed Mackay, Jordan Richards, Philip Jonathan
Visual and quantitative goodness-of-fit diagnostics are an important tool in the practitioner's toolbox. The need for convincing and reliable diagnostics is particularly clear when…
Spatial Extremes at Scale: A Case Study of Surface Skin Temperature and Heat Risk in the United States
Ben Seiyon Lee, Reetam Majumder, Jordan Richards +2
Understanding and mapping extreme heat is critical for risk management and public health planning, particularly in regions with complex terrain and heterogeneous climate. We presen…
Semi-parametric bulk and tail regression using spline-based neural networks
Reetam Majumder, Jordan Richards
Semi-parametric quantile regression (SPQR) is a flexible approach to density regression that learns a spline-based representation of conditional density functions using neural netw…
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…
Generative modelling of multivariate geometric extremes using normalising flows
Lambert De Monte, Raphaël Huser, Ioannis Papastathopoulos +1
Leveraging the recently emerging geometric approach to multivariate extremes and the flexibility of normalising flows on the hypersphere, we propose a principled deep-learning-base…